-------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\brandice\Dropbox\Brandice_Luca\Covid partisanship paper\Replication files\Luca replicate\cwrm_replication
> .log
  log type:  text
 opened on:  26 May 2025, 13:04:02

. do "C:\Users\brandice\Dropbox\Brandice_Luca\Covid partisanship paper\Replication files\Luca replicate\cwrm_replication_STATA.
> do"

. *STATA packages needed
. 
. *need the following STATA packages: ftools, reghdfe, outreg2, grc1leg, coefplot, stackdid, estpost
. * use commands lookup, ssc, and install as needed to install these packages if do not already have them
. 
. *If not created already, create figures and tables folders where output is stored
. capture mkdir "figures"

. capture mkdir "tables"

. capture mkdir "data"

. 
. *Also if not already set, set the directory for the main files, using the cd command
. *For instance, "cd "C:\Users\replication\"
. 
. ******************
. *** MANUSCRIPT ***
. ******************
. 
. ****************
. *** Figure 1 ***
. ****************
. 
. *Evolution of COVID-19 Reponses, by Political Affiliation
. 
. clear

. use "data_gallup.dta"

. 
. keep if gop==1 | dem==1
(50,335 observations deleted)

. egen year_month=concat(year month), punc(-)

. sort time gop

. collapse (first) time time_string (min) min_time=time (max) max_time=time (mean) Mostly_Isol v_worry_ill worn_mask mostly_rem
> ote [aw=WEIGHT], by(year_month gop)

. keep time year_month gop Mostly_Isol v_worry_ill worn_mask mostly_remote

. sort gop time

. 
. foreach x in Mostly_Isol v_worry_ill worn_mask mostly_remote {
  2. egen min_`x'=min(time) if `x'!=.
  3. egen max_`x'=max(min_`x')
  4. }
(2 missing values generated)
(2 missing values generated)
(2 missing values generated)

. 
. drop if year_month==""
(0 observations deleted)

. drop if gop==.
(0 observations deleted)

. 
. sort gop time 

. 
. gen time_string=time

. format time_string %td

. 
. twoway line v_worry_ill time_string if time>min_v_worry_ill & gop==0,  connect(direct) lcolor(blue*.6)  ///
> || line v_worry_ill time_string if time>min_v_worry_ill & gop==1,  connect(direct) lcolor(red*.6) lpattern(dash)  ///
> saving(g1, replace)  ytitle("") ///
> xtitle("") xlabel(21993(120)22508, grid gmax labgap(tiny)) ///
> plotregion(color(white)) graphregion(color(white)) ///
> xline(22325 22354 22389 , lwidth(.5in) lc(gray*.2)) ///
> xline(22325 22389, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> legend(label(2 "Republican") label(1 "Democrat") row(1) pos(6))  ///
> title("Very worried over COVID", span) 
(file g1.gph not found)
file g1.gph saved

. 
. twoway  line  Mostly_Isol time_string if time>min_Mostly_Isol & gop==0,  connect(direct) lcolor(blue*.6)  ///
> || line Mostly_Isol time_string if time>min_Mostly_Isol & gop==1,  connect(direct) lcolor(red*.6)  lpattern(dash) ///
>  saving(g2, replace)  ytitle("") ///
> xtitle("") xlabel(21993(120)22508, grid gmax labgap(tiny)) ///
> plotregion(color(white)) graphregion(color(white)) ///
> xline(22325 22354 22389 , lwidth(.5in) lc(gray*.2)) ///
> xline(22325 22389, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> legend(label(2 "Republican") label(1 "Democrat"))  ///
> title("Mostly isolating", span) 
(file g2.gph not found)
file g2.gph saved

. 
. twoway line  worn_mask time_string if time>min_worn_mask & gop==0,  connect(direct) lcolor(blue*.6)  ///
> || line  worn_mask time_string if time>min_worn_mask & gop==1,  connect(direct) lcolor(red*.6)  lpattern(dash) ///
> saving(g3, replace) ytitle("") ///
> xtitle("") xlabel(21993(120)22508, grid gmax labgap(tiny)) ///
> plotregion(color(white)) graphregion(color(white)) ///
> xline(22325 22354 22389 , lwidth(.5in) lc(gray*.2)) ///
> xline(22325 22389, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> legend(label(2 "Republican") label(1 "Democrat"))  ///
> title("Worn mask", span) 
(file g3.gph not found)
file g3.gph saved

. 
. twoway  line  mostly_remote time_string if time>min_mostly_remote & gop==0,  connect(direct) lcolor(blue*.6)  ///
> || line  mostly_remote time_string if time>min_mostly_remote & gop==1,  connect(direct) lcolor(red*.6)  lpattern(dash) ///
> saving(g4, replace) ytitle("") ///
> xtitle("") xlabel(21993(120)22508, grid gmax labgap(tiny)) ///
> plotregion(color(white)) graphregion(color(white)) ///
> xline(22325 22354 22389 , lwidth(.5in) lc(gray*.2)) ///
> xline(22325 22389, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> legend(label(2 "Republican") label(1 "Democrat"))  ///
> title("Mostly working remote", span) 
(file g4.gph not found)
file g4.gph saved

. 
. grc1leg  g2.gph g3.gph g1.gph   g4.gph , ///
> imargin(0.5 0.5 0.5 0.5) row(2) col(2) legendfrom(g1.gph) iscale(*.75) ///
> plotregion(color(white)) graphregion(color(white)) 

. graph export "figures\Figure 1.png", replace width(2000) height(1500)
file figures\Figure 1.png saved as PNG format

. 
. * Delete the intermediate files
. erase g1.gph

. erase g2.gph

. erase g3.gph

. erase g4.gph

. 
. *****************************
. *** Figure 2 and Table S9 ***
. *****************************
. 
. *Change in Partisan Gap in COVID-19 Responses
. 
. clear

. use "data_gallup.dta"

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(4,143 real changes made)
(3,759 real changes made)
(3,905 real changes made)
(3,731 real changes made)
(3,572 real changes made)
(4,843 real changes made)
(3,475 real changes made)
(3,553 real changes made)
(4,034 real changes made)

. egen minmonthvac=min(month_number) if vaccinated!=., by(pid)
(264 missing values generated)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(30,507 missing values generated)

. egen minmonthisol=min(month_number) if Mostly_Isol!=., by(pid)
(5,890 missing values generated)

. egen minmonthworry=min(month_number) if v_worry_ill!=., by(pid)
(35,223 missing values generated)

. egen minmonthmostly_remote=min(month_number) if mostly_remote!=., by(pid)
(108,466 missing values generated)

. 
. label variable age10 "Age (continuous)"

. label variable age_group4 "Age 65 and up (indicator)"

. label variable ZLNpc_new_cases_7day "Log Per capita COVID cases"

. label variable somecol "Some college"

. label variable Y3h6_facialcoverings "Mask required outside home"

. label variable out_workforce "Out of workforce"

. label variable income "Income"

. label variable AmerInd "American Indian of Native Hawaiian"

. label variable Yc4_restrictionsongatherings "Restrictions on social gathering in effect"

. label variable indep_third "Independent respondent"

. 
. *Mostly Isolate
. 
. estimates clear

. 
. reghdfe Mostly_Isol dmonthdum3-dmonthdum20 dem indep_third imonthdum3-imonthdum20 ZLNpc_new_cases_7day employed out_workforce
>  live_w_children income male age10 age_group4 somecol ba grad AmerInd Asian Black Hisp Multiracial Yc4_restrictionsongatherin
> gs Yc6_stayathomerequirements [aw=WEIGHT],  a(time ctyfip) vce(cl ctyfip)
(dropped 111 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =    138,455
Absorbing 2 HDFE groups                           F(  56,   2525) =      54.36
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2556
                                                  Adj R-squared   =     0.2398
                                                  Within R-sq.    =     0.0715
Number of clusters (ctyfip)  =      2,526         Root MSE        =     0.4359

                                             (Std. err. adjusted for 2,526 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum3 |   .0665058   .0202744     3.28   0.001     .0267496    .1062619
                  dmonthdum4 |   .1745045    .025087     6.96   0.000     .1253113    .2236978
                  dmonthdum5 |   .1820746   .0252986     7.20   0.000     .1324665    .2316828
                  dmonthdum6 |   .1991725   .0255534     7.79   0.000     .1490647    .2492804
                  dmonthdum7 |   .1919729   .0286206     6.71   0.000     .1358507    .2480951
                  dmonthdum8 |   .1713969   .0432742     3.96   0.000     .0865403    .2562535
                  dmonthdum9 |   .1756162   .0434365     4.04   0.000     .0904414    .2607911
                 dmonthdum10 |   .2160193   .0467195     4.62   0.000     .1244068    .3076317
                 dmonthdum11 |   .2181137   .0315004     6.92   0.000     .1563445    .2798829
                 dmonthdum12 |   .2062615   .0271228     7.60   0.000     .1530763    .2594468
                 dmonthdum13 |   .2092266   .0295691     7.08   0.000     .1512445    .2672087
                 dmonthdum14 |   .2141582   .0286742     7.47   0.000     .1579308    .2703856
                 dmonthdum15 |   .0715905   .0277148     2.58   0.010     .0172444    .1259367
                 dmonthdum16 |   .0806175   .0268448     3.00   0.003     .0279774    .1332575
                 dmonthdum17 |   .0451518   .0268733     1.68   0.093    -.0075442    .0978477
                 dmonthdum18 |   .0035636   .0264945     0.13   0.893    -.0483897    .0555168
                 dmonthdum19 |   .0609684    .028775     2.12   0.034     .0045435    .1173934
                 dmonthdum20 |   .0426309   .0279459     1.53   0.127    -.0121684    .0974301
                         dem |    .061019   .0191919     3.18   0.001     .0233856    .0986525
                 indep_third |   .0398739   .0210813     1.89   0.059    -.0014645    .0812123
                  imonthdum3 |   .0310623   .0229294     1.35   0.176    -.0139001    .0760247
                  imonthdum4 |   .0828285   .0265958     3.11   0.002     .0306767    .1349803
                  imonthdum5 |   .0937587    .027173     3.45   0.001      .040475    .1470425
                  imonthdum6 |   .1059614    .026877     3.94   0.000     .0532581    .1586647
                  imonthdum7 |    .119301     .03083     3.87   0.000     .0588464    .1797556
                  imonthdum8 |   .1044145   .0484761     2.15   0.031     .0093575    .1994715
                  imonthdum9 |   .1811757   .0487092     3.72   0.000     .0856617    .2766897
                 imonthdum10 |   .0563472   .0512001     1.10   0.271    -.0440512    .1567457
                 imonthdum11 |   .1733092   .0356755     4.86   0.000      .103353    .2432654
                 imonthdum12 |   .0779356   .0321862     2.42   0.016     .0148216    .1410496
                 imonthdum13 |   .1295573   .0320288     4.05   0.000      .066752    .1923627
                 imonthdum14 |   .1189433   .0301092     3.95   0.000     .0599021    .1779844
                 imonthdum15 |   .0901171   .0307602     2.93   0.003     .0297992    .1504349
                 imonthdum16 |   .0658035   .0277862     2.37   0.018     .0113173    .1202896
                 imonthdum17 |   .0539644   .0266871     2.02   0.043     .0016336    .1062952
                 imonthdum18 |   .0607159   .0299942     2.02   0.043     .0019001    .1195317
                 imonthdum19 |   .0376511   .0310665     1.21   0.226    -.0232673    .0985695
                 imonthdum20 |   .0462667   .0284819     1.62   0.104    -.0095836     .102117
        ZLNpc_new_cases_7day |   .0216012   .0035196     6.14   0.000     .0146997    .0285027
                    employed |  -.1673194   .0131897   -12.69   0.000    -.1931832   -.1414557
               out_workforce |   .0178929   .0147196     1.22   0.224    -.0109708    .0467567
             live_w_children |  -.0351237   .0074183    -4.73   0.000    -.0496704    -.020577
                      income |   .0043304   .0016392     2.64   0.008      .001116    .0075448
                        male |  -.0453325   .0061838    -7.33   0.000    -.0574584   -.0332067
                       age10 |  -.0177673   .0030818    -5.77   0.000    -.0238104   -.0117241
                  age_group4 |   .0090975   .0108069     0.84   0.400    -.0120938    .0302888
                     somecol |    .021045   .0084801     2.48   0.013     .0044164    .0376736
                          ba |   .0846394   .0110885     7.63   0.000     .0628959     .106383
                        grad |   .1093392   .0099223    11.02   0.000     .0898825    .1287959
                     AmerInd |  -.0198966   .0432844    -0.46   0.646    -.1047731    .0649799
                       Asian |   .0052979   .0301175     0.18   0.860    -.0537596    .0643553
                       Black |  -.0318124   .0120287    -2.64   0.008    -.0553995   -.0082254
                        Hisp |   .0045672   .0108741     0.42   0.675    -.0167559    .0258903
                 Multiracial |  -.0223519     .01796    -1.24   0.213    -.0575697    .0128659
Yc4_restrictionsongatherings |  -.0001505   .0093688    -0.02   0.987    -.0185219    .0182209
  Yc6_stayathomerequirements |   .0075564   .0079297     0.95   0.341     -.007993    .0231057
                       _cons |   .5379425   .0231017    23.29   0.000     .4926422    .5832427
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       287           1         286     |
      ctyfip |      2526        2526           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S9.xls", excel adjr2 lab dec(3) replace
tables\Table S9.xls
dir : seeout

. estimates store nofes

. 
. reghdfe Mostly_Isol  dmonthdum3-dmonthdum20 dem indep_third imonthdum3-imonthdum20  ZLNpc_new_cases_7day out_workforce employ
> ed income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT]  if minmonthisol==3 ,  a(time pid) vce(cl ctyfi
> p)
(dropped 1672 singleton observations)
(MWFE estimator converged in 11 iterations)

HDFE Linear regression                            Number of obs   =     55,026
Absorbing 2 HDFE groups                           F(  44,   1939) =       4.94
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5862
                                                  Adj R-squared   =     0.4315
                                                  Within R-sq.    =     0.0148
Number of clusters (ctyfip)  =      1,940         Root MSE        =     0.3768

                                             (Std. err. adjusted for 1,940 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum3 |   .1010606   .0268073     3.77   0.000     .0484864    .1536348
                  dmonthdum4 |   .1705595   .0343922     4.96   0.000       .10311    .2380089
                  dmonthdum5 |    .172719   .0327287     5.28   0.000     .1085317    .2369062
                  dmonthdum6 |    .175556    .034669     5.06   0.000     .1075635    .2435485
                  dmonthdum7 |   .2313938   .0405411     5.71   0.000     .1518851    .3109025
                  dmonthdum8 |   .1912055   .0760297     2.51   0.012      .042097    .3403141
                  dmonthdum9 |   .2366158   .0655287     3.61   0.000     .1081017    .3651299
                 dmonthdum10 |   .1441254   .0804024     1.79   0.073    -.0135589    .3018097
                 dmonthdum11 |    .195774   .0422335     4.64   0.000     .1129461    .2786019
                 dmonthdum12 |   .2536974   .0385203     6.59   0.000     .1781518     .329243
                 dmonthdum13 |    .172466   .0417956     4.13   0.000      .090497    .2544351
                 dmonthdum14 |   .2744329   .0436242     6.29   0.000     .1888776    .3599881
                 dmonthdum15 |   .1006475   .0497448     2.02   0.043     .0030885    .1982065
                 dmonthdum16 |   .1231356   .0459094     2.68   0.007     .0330987    .2131725
                 dmonthdum17 |   .0512932   .0418966     1.22   0.221     -.030874    .1334603
                 dmonthdum18 |     .03909   .0489075     0.80   0.424    -.0568269    .1350069
                 dmonthdum19 |   .1865717   .0489872     3.81   0.000     .0904985    .2826448
                 dmonthdum20 |   .0010015   .0486314     0.02   0.984    -.0943737    .0963767
                         dem |  -.1566209   .0323713    -4.84   0.000    -.2201071   -.0931347
                 indep_third |  -.1346705   .0272437    -4.94   0.000    -.1881004   -.0812405
                  imonthdum3 |   .0690836   .0305884     2.26   0.024     .0090941    .1290732
                  imonthdum4 |   .1314493   .0363886     3.61   0.000     .0600844    .2028141
                  imonthdum5 |   .1050831    .035709     2.94   0.003     .0350511    .1751152
                  imonthdum6 |    .132472   .0368338     3.60   0.000      .060234    .2047101
                  imonthdum7 |    .185868   .0412617     4.50   0.000     .1049461    .2667899
                  imonthdum8 |   .2356961   .0785932     3.00   0.003     .0815601     .389832
                  imonthdum9 |   .3022802   .0706505     4.28   0.000     .1637212    .4408391
                 imonthdum10 |   .0376448   .0897572     0.42   0.675    -.1383859    .2136755
                 imonthdum11 |   .1682655   .0519507     3.24   0.001     .0663804    .2701507
                 imonthdum12 |   .1655144   .0395093     4.19   0.000     .0880292    .2429995
                 imonthdum13 |   .1923299   .0444244     4.33   0.000     .1052052    .2794546
                 imonthdum14 |   .1967485   .0520898     3.78   0.000     .0945906    .2989064
                 imonthdum15 |   .1174865   .0582871     2.02   0.044     .0031745    .2317984
                 imonthdum16 |   .1418479   .0468892     3.03   0.003     .0498894    .2338064
                 imonthdum17 |   .1108793   .0393766     2.82   0.005     .0336543    .1881042
                 imonthdum18 |   .1282836   .0537125     2.39   0.017     .0229433     .233624
                 imonthdum19 |   .1917902    .049298     3.89   0.000     .0951074    .2884729
                 imonthdum20 |   .0308145   .0471592     0.65   0.514    -.0616735    .1233025
        ZLNpc_new_cases_7day |   .0222051   .0057867     3.84   0.000     .0108563    .0335539
               out_workforce |  -.0002696   .0381833    -0.01   0.994    -.0751541     .074615
                    employed |  -.0955687   .0320357    -2.98   0.003    -.1583967   -.0327406
                      income |  -.0032143   .0061826    -0.52   0.603    -.0153395    .0089109
Yc4_restrictionsongatherings |   .0061391   .0147996     0.41   0.678    -.0228857    .0351639
  Yc6_stayathomerequirements |   .0072371   .0117734     0.61   0.539    -.0158528     .030327
                       _cons |   .6130549   .0530164    11.56   0.000     .5090799      .71703
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       274           1         273     |
         pid |     14659       14659           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S9.xls", excel adjr2 lab dec(3)
tables\Table S9.xls
dir : seeout

. estimates store fes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("MostlyIsolate", replace) ///
> title("Mostly Isolating (base month March 2020)") xtitle("Pandemic Month")
(file MostlyIsolate.gph not found)
file MostlyIsolate.gph saved

. 
. 
. *Worn Mask
. 
. estimates clear

. 
. reghdfe worn_mask  dmonthdum4-dmonthdum20 dem indep_third imonthdum4-imonthdum20 ZLNpc_new_cases_7day out_workforce employed 
> live_w_children income  Y3h6_facialcoverings male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial [aw
> =WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 121 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =    118,436
Absorbing 2 HDFE groups                           F(  53,   2500) =      37.21
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3039
                                                  Adj R-squared   =     0.2869
                                                  Within R-sq.    =     0.0794
Number of clusters (ctyfip)  =      2,501         Root MSE        =     0.3349

                                     (Std. err. adjusted for 2,501 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
          dmonthdum4 |   .0366722   .0187004     1.96   0.050     2.37e-06    .0733421
          dmonthdum5 |   .0587944    .019473     3.02   0.003     .0206096    .0969793
          dmonthdum6 |  -.0301096   .0185132    -1.63   0.104    -.0664123    .0061931
          dmonthdum7 |  -.0780408    .019088    -4.09   0.000    -.1154707   -.0406109
          dmonthdum8 |  -.1058792   .0277068    -3.82   0.000    -.1602098   -.0515486
          dmonthdum9 |   -.006254   .0324087    -0.19   0.847    -.0698046    .0572966
         dmonthdum10 |  -.0272752   .0282633    -0.97   0.335     -.082697    .0281467
         dmonthdum11 |  -.0467064   .0225446    -2.07   0.038    -.0909143   -.0024984
         dmonthdum12 |  -.0723216   .0213308    -3.39   0.001    -.1141494   -.0304937
         dmonthdum13 |  -.0319683   .0226078    -1.41   0.157    -.0763002    .0123636
         dmonthdum14 |  -.0218481   .0201612    -1.08   0.279    -.0613824    .0176863
         dmonthdum15 |    .015114   .0249596     0.61   0.545    -.0338296    .0640577
         dmonthdum16 |   .1166512    .024769     4.71   0.000     .0680813    .1652211
         dmonthdum17 |   .2033608   .0226345     8.98   0.000     .1589764    .2477452
         dmonthdum18 |   .2273511   .0301162     7.55   0.000     .1682959    .2864063
         dmonthdum19 |   .2691021   .0274339     9.81   0.000     .2153066    .3228976
         dmonthdum20 |   .2338261   .0240288     9.73   0.000     .1867078    .2809444
                 dem |   .1692286   .0144018    11.75   0.000      .140988    .1974693
         indep_third |    .082546   .0160094     5.16   0.000     .0511529    .1139391
          imonthdum4 |     .01693   .0240748     0.70   0.482    -.0302785    .0641385
          imonthdum5 |   .0235053   .0231481     1.02   0.310     -.021886    .0688967
          imonthdum6 |  -.0017068   .0215511    -0.08   0.937    -.0439666     .040553
          imonthdum7 |  -.0116722    .022305    -0.52   0.601    -.0554104     .032066
          imonthdum8 |  -.1000061   .0381239    -2.62   0.009    -.1747637   -.0252484
          imonthdum9 |  -.0176722   .0436084    -0.41   0.685    -.1031845      .06784
         imonthdum10 |   -.009284   .0363297    -0.26   0.798    -.0805234    .0619553
         imonthdum11 |   .0009843   .0263385     0.04   0.970    -.0506633    .0526319
         imonthdum12 |  -.0284885   .0251899    -1.13   0.258    -.0778837    .0209067
         imonthdum13 |  -.0350208   .0273708    -1.28   0.201    -.0886925    .0186508
         imonthdum14 |   .0184496   .0240477     0.77   0.443    -.0287058    .0656049
         imonthdum15 |  -.0032125   .0280523    -0.11   0.909    -.0582207    .0517956
         imonthdum16 |    .052241   .0313312     1.67   0.096    -.0091968    .1136787
         imonthdum17 |   .1065936   .0293106     3.64   0.000     .0491181     .164069
         imonthdum18 |   .0980649   .0344248     2.85   0.004     .0305609    .1655689
         imonthdum19 |   .1008804   .0326952     3.09   0.002     .0367679     .164993
         imonthdum20 |   .1133288   .0287164     3.95   0.000     .0570183    .1696392
ZLNpc_new_cases_7day |   .0318423   .0036664     8.68   0.000     .0246529    .0390318
       out_workforce |   .0005111   .0117315     0.04   0.965    -.0224933    .0235156
            employed |  -.0083697    .010005    -0.84   0.403    -.0279886    .0112492
     live_w_children |  -.0211884   .0059828    -3.54   0.000    -.0329203   -.0094566
              income |  -.0011324   .0012928    -0.88   0.381    -.0036675    .0014026
Y3h6_facialcoverings |   .0160996   .0066167     2.43   0.015     .0031249    .0290743
                male |  -.0488764   .0048582   -10.06   0.000    -.0584028     -.03935
               age10 |   .0105593    .002849     3.71   0.000     .0049726     .016146
          age_group4 |   .0178283   .0098157     1.82   0.069    -.0014195    .0370761
             somecol |   .0332536   .0074588     4.46   0.000     .0186275    .0478797
                  ba |   .0664137   .0078787     8.43   0.000     .0509642    .0818631
                grad |   .0743064   .0073269    10.14   0.000     .0599391    .0886738
             AmerInd |    .016178   .0431716     0.37   0.708    -.0684778    .1008339
               Asian |   .0352444   .0171121     2.06   0.040      .001689    .0687999
               Black |   .0170587   .0081419     2.10   0.036     .0010931    .0330243
                Hisp |   .0062761   .0071021     0.88   0.377    -.0076505    .0202027
         Multiracial |  -.0178514   .0168989    -1.06   0.291    -.0509886    .0152858
               _cons |   .6294598   .0179422    35.08   0.000     .5942767    .6646428
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       269           1         268     |
      ctyfip |      2501        2501           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S9.xls", excel adjr2 lab dec(3)
tables\Table S9.xls
dir : seeout

. estimates store nofes

. 
. reghdfe worn_mask dmonthdum4-dmonthdum20 dem indep_third imonthdum4-imonthdum20  ZLNpc_new_cases_7day out_workforce employed 
> income  Y3h6_facialcoverings [aw=WEIGHT]  if minmonthmask==4  , a(time pid) vce(cl ctyfip)
(dropped 3832 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     65,975
Absorbing 2 HDFE groups                           F(  41,   2149) =       8.55
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6222
                                                  Adj R-squared   =     0.4462
                                                  Within R-sq.    =     0.0211
Number of clusters (ctyfip)  =      2,150         Root MSE        =     0.3040

                                     (Std. err. adjusted for 2,150 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
          dmonthdum4 |   .0593379   .0274246     2.16   0.031     .0055563    .1131195
          dmonthdum5 |   .0869463   .0244685     3.55   0.000      .038962    .1349307
          dmonthdum6 |   -.014265   .0225365    -0.63   0.527    -.0584605    .0299306
          dmonthdum7 |  -.0543597   .0239624    -2.27   0.023    -.1013516   -.0073678
          dmonthdum8 |  -.0816948   .0410876    -1.99   0.047    -.1622703   -.0011193
          dmonthdum9 |  -.0074517   .0418183    -0.18   0.859    -.0894603    .0745569
         dmonthdum10 |  -.0282842   .0323174    -0.88   0.382    -.0916609    .0350924
         dmonthdum11 |    .015155   .0287092     0.53   0.598    -.0411457    .0714557
         dmonthdum12 |  -.0745412    .027784    -2.68   0.007    -.1290274   -.0200549
         dmonthdum13 |  -.0103923   .0316237    -0.33   0.742    -.0724086     .051624
         dmonthdum14 |  -.0227798   .0293281    -0.78   0.437    -.0802942    .0347346
         dmonthdum15 |   .0195452   .0332391     0.59   0.557     -.045639    .0847293
         dmonthdum16 |   .1268244   .0361008     3.51   0.000     .0560283    .1976206
         dmonthdum17 |   .2102053    .033571     6.26   0.000     .1443702    .2760404
         dmonthdum18 |   .2168345   .0452687     4.79   0.000     .1280595    .3056094
         dmonthdum19 |   .2504275   .0385633     6.49   0.000     .1748022    .3260528
         dmonthdum20 |   .2305409   .0321544     7.17   0.000     .1674838    .2935979
                 dem |  -.0711372   .0268234    -2.65   0.008    -.1237397   -.0185347
         indep_third |   -.075222    .025158    -2.99   0.003    -.1245585   -.0258855
          imonthdum4 |   .0664256   .0319776     2.08   0.038     .0037154    .1291358
          imonthdum5 |   .0495043   .0265222     1.87   0.062    -.0025077    .1015162
          imonthdum6 |   .0292369   .0259159     1.13   0.259    -.0215859    .0800597
          imonthdum7 |  -.0178958   .0279308    -0.64   0.522      -.07267    .0368783
          imonthdum8 |  -.0942882   .0458526    -2.06   0.040    -.1842082   -.0043681
          imonthdum9 |  -.0228955   .0523845    -0.44   0.662    -.1256251     .079834
         imonthdum10 |   .0440287   .0412177     1.07   0.286    -.0368021    .1248595
         imonthdum11 |   .0976878   .0368827     2.65   0.008     .0253583    .1700173
         imonthdum12 |  -.0210032   .0301904    -0.70   0.487    -.0802086    .0382021
         imonthdum13 |   .0316018   .0371041     0.85   0.394    -.0411618    .1043654
         imonthdum14 |    .013345   .0333238     0.40   0.689    -.0520053    .0786953
         imonthdum15 |   .0463099   .0384767     1.20   0.229    -.0291455    .1217653
         imonthdum16 |    .091246    .041951     2.18   0.030     .0089772    .1735147
         imonthdum17 |   .0669514   .0418727     1.60   0.110    -.0151638    .1490667
         imonthdum18 |   .1159992   .0509111     2.28   0.023     .0161589    .2158394
         imonthdum19 |   .1311693   .0458321     2.86   0.004     .0412893    .2210492
         imonthdum20 |   .0904038   .0378267     2.39   0.017      .016223    .1645846
ZLNpc_new_cases_7day |   .0361017    .005158     7.00   0.000     .0259864     .046217
       out_workforce |   .0033903   .0272244     0.12   0.901    -.0499986    .0567791
            employed |   .0196658   .0236751     0.83   0.406    -.0267626    .0660942
              income |  -.0049402   .0044335    -1.11   0.265    -.0136345    .0037542
Y3h6_facialcoverings |   .0180211   .0092622     1.95   0.052    -.0001427     .036185
               _cons |   .8212228   .0368429    22.29   0.000     .7489713    .8934743
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       268           1         267     |
         pid |     20664       20664           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S9.xls", excel adjr2 lab dec(3)
tables\Table S9.xls
dir : seeout

. estimates store fes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Mask", replace) ///
> title("Worn mask (base month April 2020)") xtitle("Pandemic Month")
(file Mask.gph not found)
file Mask.gph saved

. 
. 
. *Very Worried Ill
. 
. estimates clear

. 
. reghdfe v_worry_ill dmonthdum4-dmonthdum20 dem indep_third imonthdum4-imonthdum20 ZLNpc_new_cases_7day out_workforce employed
>  live_w_children income Yc4_restrictionsongatherings Yc6_stayathomerequirements male age10 age_group4   somecol ba grad AmerI
> nd Asian Black Hisp Multiracial  [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 126 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =    114,250
Absorbing 2 HDFE groups                           F(  54,   2488) =      17.52
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1360
                                                  Adj R-squared   =     0.1142
                                                  Within R-sq.    =     0.0380
Number of clusters (ctyfip)  =      2,489         Root MSE        =     0.2871

                                             (Std. err. adjusted for 2,489 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum4 |     .00661   .0148947     0.44   0.657    -.0225973    .0358172
                  dmonthdum5 |   -.002444   .0144171    -0.17   0.865    -.0307147    .0258268
                  dmonthdum6 |    .067362   .0160173     4.21   0.000     .0359535    .0987706
                  dmonthdum7 |   .0534984   .0176273     3.03   0.002     .0189328     .088064
                  dmonthdum8 |   .0279893    .030622     0.91   0.361    -.0320579    .0880366
                  dmonthdum9 |   .0425501    .027289     1.56   0.119    -.0109613    .0960615
                 dmonthdum10 |   .0779251   .0321889     2.42   0.016     .0148052     .141045
                 dmonthdum11 |   .0506245   .0211754     2.39   0.017     .0091013    .0921477
                 dmonthdum12 |   .0395838   .0176217     2.25   0.025     .0050291    .0741384
                 dmonthdum13 |   .0344683   .0201107     1.71   0.087    -.0049671    .0739037
                 dmonthdum14 |  -.0209032   .0165136    -1.27   0.206    -.0532851    .0114787
                 dmonthdum15 |  -.0536068   .0145558    -3.68   0.000    -.0821496    -.025064
                 dmonthdum16 |  -.0824034   .0150767    -5.47   0.000    -.1119676   -.0528392
                 dmonthdum17 |  -.0799365   .0138284    -5.78   0.000    -.1070528   -.0528202
                 dmonthdum18 |  -.0769909   .0159508    -4.83   0.000    -.1082692   -.0457126
                 dmonthdum19 |  -.0452192   .0179979    -2.51   0.012    -.0805115   -.0099268
                 dmonthdum20 |  -.0457123   .0157989    -2.89   0.004    -.0766927    -.014732
                         dem |   .1046735   .0120606     8.68   0.000     .0810237    .1283233
                 indep_third |   .0381913   .0117979     3.24   0.001     .0150566    .0613261
                  imonthdum4 |   .0092024   .0152165     0.60   0.545     -.020636    .0390407
                  imonthdum5 |   .0122144   .0141827     0.86   0.389    -.0155966    .0400254
                  imonthdum6 |   .0533886   .0164583     3.24   0.001     .0211152     .085662
                  imonthdum7 |   .0493641   .0167358     2.95   0.003     .0165466    .0821816
                  imonthdum8 |  -.0218272   .0253922    -0.86   0.390    -.0716191    .0279648
                  imonthdum9 |   .0322608   .0283761     1.14   0.256    -.0233823     .087904
                 imonthdum10 |   .0547287    .030383     1.80   0.072    -.0048499    .1143072
                 imonthdum11 |   .0117794    .021159     0.56   0.578    -.0297116    .0532705
                 imonthdum12 |   .0147218   .0173127     0.85   0.395    -.0192269    .0486706
                 imonthdum13 |   .0225251   .0181651     1.24   0.215    -.0130952    .0581454
                 imonthdum14 |   .0101099   .0144661     0.70   0.485     -.018257    .0384769
                 imonthdum15 |     .01086   .0148682     0.73   0.465    -.0182953    .0400152
                 imonthdum16 |  -.0325611   .0132042    -2.47   0.014    -.0584534   -.0066687
                 imonthdum17 |  -.0169065   .0134993    -1.25   0.211    -.0433775    .0095645
                 imonthdum18 |  -.0059616   .0150181    -0.40   0.691    -.0354109    .0234877
                 imonthdum19 |  -.0232543   .0162197    -1.43   0.152    -.0550598    .0085511
                 imonthdum20 |   .0081999   .0156822     0.52   0.601    -.0225516    .0389514
        ZLNpc_new_cases_7day |    .011628    .002775     4.19   0.000     .0061863    .0170696
               out_workforce |  -.0331538   .0118731    -2.79   0.005     -.056436   -.0098716
                    employed |  -.0359545   .0112694    -3.19   0.001    -.0580528   -.0138562
             live_w_children |   .0020399   .0053747     0.38   0.704    -.0084994    .0125793
                      income |  -.0054673   .0011286    -4.84   0.000    -.0076804   -.0032543
Yc4_restrictionsongatherings |  -.0030537     .00675    -0.45   0.651    -.0162898    .0101824
  Yc6_stayathomerequirements |   .0013986   .0056225     0.25   0.804    -.0096266    .0124239
                        male |  -.0408498   .0052082    -7.84   0.000    -.0510626    -.030637
                       age10 |  -.0011877   .0022735    -0.52   0.601    -.0056458    .0032704
                  age_group4 |  -.0254015   .0089525    -2.84   0.005    -.0429566   -.0078465
                     somecol |   .0118981   .0062388     1.91   0.057    -.0003357    .0241319
                          ba |   .0005625   .0071828     0.08   0.938    -.0135223    .0146473
                        grad |    .011264   .0075135     1.50   0.134    -.0034694    .0259974
                     AmerInd |   .0169255   .0293412     0.58   0.564    -.0406102    .0744612
                       Asian |   .0288802   .0298466     0.97   0.333    -.0296466     .087407
                       Black |  -.0082704   .0093547    -0.88   0.377    -.0266143    .0100734
                        Hisp |   .0188816   .0087182     2.17   0.030     .0017858    .0359774
                 Multiracial |   .0231919   .0127005     1.83   0.068    -.0017127    .0480965
                       _cons |   .1290021   .0166917     7.73   0.000     .0962709    .1617332
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       265           1         264     |
      ctyfip |      2489        2489           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S9.xls", excel adjr2 lab dec(3)
tables\Table S9.xls
dir : seeout

. estimates store nofes

. 
. reghdfe v_worry_ill dmonthdum4-dmonthdum20 dem indep_third imonthdum4-imonthdum20  ZLNpc_new_cases_7day out_workforce employe
> d income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT]  if minmonthworry==4  , a(time pid) vce(cl ctyfi
> p)
(dropped 3181 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     53,892
Absorbing 2 HDFE groups                           F(  42,   2030) =       4.34
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6417
                                                  Adj R-squared   =     0.4731
                                                  Within R-sq.    =     0.0125
Number of clusters (ctyfip)  =      2,031         Root MSE        =     0.2223

                                             (Std. err. adjusted for 2,031 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum4 |  -.0283971   .0178538    -1.59   0.112    -.0634108    .0066166
                  dmonthdum5 |  -.0200062   .0156989    -1.27   0.203    -.0507937    .0107813
                  dmonthdum6 |   .0465667   .0189563     2.46   0.014     .0093909    .0837424
                  dmonthdum7 |   .0580364   .0177506     3.27   0.001     .0232251    .0928476
                  dmonthdum8 |   .0678837   .0379012     1.79   0.073    -.0064456     .142213
                  dmonthdum9 |   .1031961   .0317096     3.25   0.001     .0410094    .1653828
                 dmonthdum10 |   .0767488   .0448407     1.71   0.087    -.0111898    .1646874
                 dmonthdum11 |   .0210712   .0267197     0.79   0.430    -.0313296     .073472
                 dmonthdum12 |    .005604   .0221285     0.25   0.800    -.0377929    .0490008
                 dmonthdum13 |   .0133739   .0269336     0.50   0.620    -.0394463    .0661942
                 dmonthdum14 |  -.0533173   .0216914    -2.46   0.014     -.095857   -.0107776
                 dmonthdum15 |  -.0600368   .0231951    -2.59   0.010    -.1055254   -.0145481
                 dmonthdum16 |  -.1279133   .0230459    -5.55   0.000    -.1731094   -.0827172
                 dmonthdum17 |  -.0854412   .0192252    -4.44   0.000    -.1231443    -.047738
                 dmonthdum18 |  -.0873809   .0279529    -3.13   0.002    -.1422003   -.0325616
                 dmonthdum19 |  -.0644211   .0273729    -2.35   0.019    -.1181029   -.0107392
                 dmonthdum20 |  -.0712826   .0233387    -3.05   0.002    -.1170529   -.0255123
                         dem |   .0261601   .0173872     1.50   0.133    -.0079385    .0602587
                 indep_third |  -.0203861   .0116189    -1.75   0.079    -.0431724    .0024002
                  imonthdum4 |   .0224644   .0199186     1.13   0.260    -.0165987    .0615275
                  imonthdum5 |   .0360655   .0166119     2.17   0.030     .0034874    .0686436
                  imonthdum6 |   .0601537   .0192193     3.13   0.002      .022462    .0978454
                  imonthdum7 |   .0301986   .0185416     1.63   0.104    -.0061639    .0665611
                  imonthdum8 |   .0298561   .0330025     0.90   0.366    -.0348662    .0945783
                  imonthdum9 |   .0778971   .0367745     2.12   0.034     .0057774    .1500168
                 imonthdum10 |   .0171154   .0397536     0.43   0.667    -.0608467    .0950775
                 imonthdum11 |  -.0081065   .0243957    -0.33   0.740    -.0559497    .0397366
                 imonthdum12 |   .0340311   .0224501     1.52   0.130    -.0099966    .0780588
                 imonthdum13 |   .0359942   .0217529     1.65   0.098    -.0066662    .0786546
                 imonthdum14 |   .0012564   .0180617     0.07   0.945     -.034165    .0366779
                 imonthdum15 |   .0393241   .0228666     1.72   0.086    -.0055202    .0841685
                 imonthdum16 |   .0006341   .0229012     0.03   0.978    -.0442782    .0455464
                 imonthdum17 |  -.0009981    .021768    -0.05   0.963    -.0436881    .0416918
                 imonthdum18 |   .0151108   .0217974     0.69   0.488    -.0276367    .0578583
                 imonthdum19 |   .0070249   .0209804     0.33   0.738    -.0341205    .0481704
                 imonthdum20 |   .0076423   .0202477     0.38   0.706    -.0320662    .0473507
        ZLNpc_new_cases_7day |   .0102603    .003616     2.84   0.005     .0031689    .0173517
               out_workforce |  -.0358973   .0223295    -1.61   0.108    -.0796884    .0078939
                    employed |  -.0319495    .019935    -1.60   0.109    -.0710446    .0071456
                      income |  -.0016967   .0034355    -0.49   0.621    -.0084342    .0050408
Yc4_restrictionsongatherings |  -.0029942   .0110589    -0.27   0.787    -.0246822    .0186938
  Yc6_stayathomerequirements |   .0098692   .0076767     1.29   0.199    -.0051858    .0249242
                       _cons |   .1324299   .0258739     5.12   0.000     .0816877    .1831722
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       256           1         255     |
         pid |     16946       16946           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S9.xls", excel adjr2 lab dec(3)
tables\Table S9.xls
dir : seeout

. estimates store fes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Worry", replace) ///
> title("Very worried about COVID (base month April 2020)") xtitle("Pandemic Month")
(file Worry.gph not found)
file Worry.gph saved

. 
. 
. *Mostly Remote
. 
. estimates clear

. 
. reghdfe mostly_remote dmonthdum5-dmonthdum20  dem indep_third imonthdum5-imonthdum20 ZLNpc_new_cases_7day  live_w_children in
> come Yc4_restrictionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing  male age10 age_group4   somecol ba grad Am
> erInd Asian Black Hisp Multiracial  if  employed==1 [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 242 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     51,933
Absorbing 2 HDFE groups                           F(  51,   1980) =      41.17
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3179
                                                  Adj R-squared   =     0.2866
                                                  Within R-sq.    =     0.1235
Number of clusters (ctyfip)  =      1,981         Root MSE        =     0.4191

                                             (Std. err. adjusted for 1,981 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum5 |   .0081303   .0286966     0.28   0.777    -.0481485     .064409
                  dmonthdum6 |   .0043257   .0274611     0.16   0.875      -.04953    .0581815
                  dmonthdum7 |   .0140289   .0319702     0.44   0.661    -.0486699    .0767277
                  dmonthdum8 |   .0893791   .0545296     1.64   0.101    -.0175623    .1963205
                  dmonthdum9 |  -.0367341    .061425    -0.60   0.550    -.1571985    .0837303
                 dmonthdum10 |   .0463816   .0530123     0.87   0.382    -.0575842    .1503474
                 dmonthdum11 |   .0111225   .0392895     0.28   0.777    -.0659306    .0881757
                 dmonthdum12 |  -.0332924   .0367169    -0.91   0.365    -.1053003    .0387155
                 dmonthdum13 |  -.0193015   .0348117    -0.55   0.579    -.0875729    .0489698
                 dmonthdum14 |  -.0218031   .0376729    -0.58   0.563    -.0956858    .0520795
                 dmonthdum15 |  -.0763555   .0368872    -2.07   0.039    -.1486973   -.0040137
                 dmonthdum16 |  -.0731229   .0344796    -2.12   0.034    -.1407431   -.0055027
                 dmonthdum17 |  -.0359417   .0359595    -1.00   0.318    -.1064642    .0345808
                 dmonthdum18 |  -.0648176   .0358393    -1.81   0.071    -.1351042    .0054691
                 dmonthdum19 |  -.0199326   .0390787    -0.51   0.610    -.0965723     .056707
                 dmonthdum20 |  -.1214355    .035501    -3.42   0.001    -.1910587   -.0518123
                         dem |   .1394122   .0208088     6.70   0.000     .0986027    .1802216
                 indep_third |   .0772709   .0220758     3.50   0.000     .0339766    .1205652
                  imonthdum5 |  -.0046657   .0343468    -0.14   0.892    -.0720253     .062694
                  imonthdum6 |  -.0215841   .0303918    -0.71   0.478    -.0811874    .0380192
                  imonthdum7 |   .0123701   .0341978     0.36   0.718    -.0546973    .0794375
                  imonthdum8 |   .0776352   .0560055     1.39   0.166    -.0322007     .187471
                  imonthdum9 |   -.017246   .0659148    -0.26   0.794    -.1465157    .1120237
                 imonthdum10 |  -.0187215   .0487822    -0.38   0.701    -.1143914    .0769485
                 imonthdum11 |  -.0292246   .0379528    -0.77   0.441    -.1036562    .0452069
                 imonthdum12 |  -.0806039   .0352366    -2.29   0.022    -.1497087   -.0114992
                 imonthdum13 |  -.0459189   .0361736    -1.27   0.204    -.1168612    .0250235
                 imonthdum14 |  -.0272508   .0363389    -0.75   0.453    -.0985173    .0440157
                 imonthdum15 |  -.0058062   .0389001    -0.15   0.881    -.0820956    .0704831
                 imonthdum16 |  -.1218122   .0381294    -3.19   0.001    -.1965902   -.0470341
                 imonthdum17 |   .0080383   .0363215     0.22   0.825     -.063194    .0792706
                 imonthdum18 |  -.0294878   .0422255    -0.70   0.485    -.1122988    .0533233
                 imonthdum19 |  -.0188486    .036875    -0.51   0.609    -.0911665    .0534694
                 imonthdum20 |  -.0734204   .0355926    -2.06   0.039    -.1432233   -.0036175
        ZLNpc_new_cases_7day |  -.0009017     .00557    -0.16   0.871    -.0118255     .010022
             live_w_children |  -.0362725   .0105023    -3.45   0.001    -.0568693   -.0156757
                      income |   .0354891   .0025359    13.99   0.000     .0305157    .0404625
Yc4_restrictionsongatherings |   .0079553   .0125373     0.63   0.526    -.0166323     .032543
  Yc6_stayathomerequirements |   .0049353   .0116195     0.42   0.671    -.0178523     .027723
        Yc2_workplaceclosing |  -.0052185   .0089374    -0.58   0.559    -.0227463    .0123092
                        male |  -.0985137   .0103585    -9.51   0.000    -.1188284    -.078199
                       age10 |   -.017333   .0045416    -3.82   0.000    -.0262399   -.0084261
                  age_group4 |   .0115439   .0193136     0.60   0.550    -.0263333     .049421
                     somecol |   .0547173   .0145387     3.76   0.000     .0262046      .08323
                          ba |   .2346352   .0172648    13.59   0.000     .2007761    .2684942
                        grad |   .2455549   .0163632    15.01   0.000      .213464    .2776458
                     AmerInd |  -.0965993   .0619069    -1.56   0.119    -.2180088    .0248102
                       Asian |   .0859104   .0485384     1.77   0.077    -.0092813    .1811021
                       Black |    .019157   .0177831     1.08   0.281    -.0157185    .0540326
                        Hisp |  -.0145494   .0196179    -0.74   0.458    -.0530232    .0239245
                 Multiracial |   -.060424   .0248861    -2.43   0.015    -.1092296   -.0116183
                       _cons |   .1601914   .0306275     5.23   0.000      .100126    .2202568
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       248           1         247     |
      ctyfip |      1981        1981           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. outreg2 using "tables\Table S9.xls", excel adjr2 lab dec(3)
tables\Table S9.xls
dir : seeout

. 
. reghdfe mostly_remote dmonthdum5-dmonthdum20 dem indep_third imonthdum5-imonthdum20  ZLNpc_new_cases_7day income Yc4_restrict
> ionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing  [aw=WEIGHT]  if (minmonthmostly_remote==4 | minmonthmostly_
> remote==5)  &  employed==1, a(time pid) vce(cl ctyfip)
(dropped 2118 singleton observations)
(MWFE estimator converged in 13 iterations)

HDFE Linear regression                            Number of obs   =     21,566
Absorbing 2 HDFE groups                           F(  39,   1437) =       0.96
Statistics robust to heteroskedasticity           Prob > F        =     0.5344
                                                  R-squared       =     0.8038
                                                  Adj R-squared   =     0.7021
                                                  Within R-sq.    =     0.0042
Number of clusters (ctyfip)  =      1,438         Root MSE        =     0.2727

                                             (Std. err. adjusted for 1,438 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum5 |  -.0030543   .0314081    -0.10   0.923    -.0646649    .0585562
                  dmonthdum6 |  -.0004066   .0303578    -0.01   0.989     -.059957    .0591438
                  dmonthdum7 |   .0282925   .0364515     0.78   0.438    -.0432113    .0997963
                  dmonthdum8 |  -.0609731   .0628971    -0.97   0.333    -.1843532     .062407
                  dmonthdum9 |  -.0621721   .0605946    -1.03   0.305    -.1810355    .0566913
                 dmonthdum10 |   .0607383   .0717028     0.85   0.397    -.0799151    .2013917
                 dmonthdum11 |  -.0661789   .0404746    -1.64   0.102    -.1455746    .0132168
                 dmonthdum12 |  -.0625459   .0432837    -1.45   0.149     -.147452    .0223602
                 dmonthdum13 |  -.0215312   .0360072    -0.60   0.550    -.0921635     .049101
                 dmonthdum14 |   .0280916   .0433099     0.65   0.517    -.0568657     .113049
                 dmonthdum15 |  -.0837657   .0498463    -1.68   0.093    -.1815449    .0140136
                 dmonthdum16 |  -.0251341   .0461934    -0.54   0.586    -.1157478    .0654795
                 dmonthdum17 |    .007426   .0473013     0.16   0.875     -.085361    .1002129
                 dmonthdum18 |  -.0219218   .0535035    -0.41   0.682    -.1268751    .0830314
                 dmonthdum19 |   .0127181   .0609067     0.21   0.835    -.1067575    .1321936
                 dmonthdum20 |  -.0998249    .049616    -2.01   0.044    -.1971525   -.0024973
                         dem |   .0184195   .0320298     0.58   0.565    -.0444106    .0812496
                 indep_third |   .0106622   .0268304     0.40   0.691    -.0419689    .0632932
                  imonthdum5 |  -.0205746   .0351384    -0.59   0.558    -.0895026    .0483535
                  imonthdum6 |  -.0232531   .0329381    -0.71   0.480    -.0878649    .0413588
                  imonthdum7 |  -.0152878   .0324837    -0.47   0.638    -.0790084    .0484327
                  imonthdum8 |  -.0970407   .0666458    -1.46   0.146    -.2277741    .0336927
                  imonthdum9 |  -.0948171   .0588496    -1.61   0.107    -.2102574    .0206232
                 imonthdum10 |   .0489443   .0634106     0.77   0.440     -.075443    .1733317
                 imonthdum11 |  -.0591954   .0433586    -1.37   0.172    -.1442483    .0258575
                 imonthdum12 |  -.0529729   .0482273    -1.10   0.272    -.1475763    .0416305
                 imonthdum13 |  -.0350456   .0427566    -0.82   0.413    -.1189176    .0488264
                 imonthdum14 |  -.0052603   .0437872    -0.12   0.904    -.0911539    .0806333
                 imonthdum15 |  -.0345441   .0571963    -0.60   0.546    -.1467413    .0776531
                 imonthdum16 |    .016441   .0545542     0.30   0.763    -.0905733    .1234554
                 imonthdum17 |   .0159918   .0458732     0.35   0.727    -.0739938    .1059774
                 imonthdum18 |   .0441107   .0535213     0.82   0.410    -.0608775    .1490989
                 imonthdum19 |   .0001563    .063733     0.00   0.998    -.1248634    .1251761
                 imonthdum20 |  -.1208385   .0509438    -2.37   0.018    -.2207706   -.0209064
        ZLNpc_new_cases_7day |  -.0040423   .0074665    -0.54   0.588    -.0186888    .0106042
                      income |   .0004872    .006874     0.07   0.944    -.0129969    .0139714
Yc4_restrictionsongatherings |  -.0178938   .0167502    -1.07   0.286    -.0507512    .0149637
  Yc6_stayathomerequirements |  -.0054589   .0126014    -0.43   0.665    -.0301779    .0192602
        Yc2_workplaceclosing |    .005757   .0120543     0.48   0.633    -.0178889    .0294029
                       _cons |   .4865893   .0515949     9.43   0.000     .3853799    .5877987
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       238           1         237     |
         pid |      7089        7089           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. outreg2 using "tables\Table S9.xls", excel adjr2 lab dec(3)
tables\Table S9.xls
dir : seeout

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> yscale(range(-.3 .2)) ylabel(-.3(.1).2) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Remote", replace) ///
> title("Mostly working remote (base month May 2020)") xtitle("Pandemic Month")
(file Remote.gph not found)
file Remote.gph saved

. 
. grc1leg MostlyIsolate.gph Mask.gph Worry.gph Remote.gph   ///
> , imargin(2 2 2 2) row(2) col(2) legendfrom(MostlyIsolate.gph) iscale(*.75) plotregion(color(white)) graphregion(color(white)
> )  

. graph export "figures\Figure 2.png", replace width(2200) height(1600)
file figures\Figure 2.png saved as PNG format

. 
. * Delete the intermediate files
. erase MostlyIsolate.gph

. erase Mask.gph

. erase Worry.gph

. erase Remote.gph

. 
. 
. ***************
. *** Table 1 ***
. ***************
. 
. *Pre- versus Post- Vaccination Status, Difference-in-Differences
. 
. clear

. use "data_gallup.dta"

. 
. // Key variables
. gen vac_dem=vaccinated*dem
(9,310 missing values generated)

. gen vac_ind=vaccinated*indep_third
(9,310 missing values generated)

. gen vac_gop=vaccinated*gop
(9,310 missing values generated)

. 
. label variable vac_dem "Vaccinated x Democrat"

. label variable vac_ind "Vaccinated x Independent"

. label variable vaccinated "Vaccinated"

. 
. **Top panel
. // Estimate TWFE model on ever and never treated
. reghdfe Mostly_Isol vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restric
> tionsongatherings Yc6_stayathomerequirements [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 12661 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =    128,789
Absorbing 2 HDFE groups                           F(  11,  37905) =      16.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6051
                                                  Adj R-squared   =     0.4386
                                                  Within R-sq.    =     0.0063
Number of clusters (pid)     =     37,906         Root MSE        =     0.3746

                                               (Std. err. adjusted for 37,906 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0411427   .0147292    -2.79   0.005    -.0700124    -.012273
                     vac_ind |  -.0099183   .0161799    -0.61   0.540    -.0416314    .0217947
                  vaccinated |  -.0610346   .0132415    -4.61   0.000    -.0869882   -.0350809
                         dem |   -.018949   .0178497    -1.06   0.288    -.0539349     .016037
                 indep_third |  -.0199478   .0129267    -1.54   0.123    -.0452845    .0053889
        ZLNpc_new_cases_7day |   .0172329   .0039154     4.40   0.000     .0095586    .0249072
               out_workforce |  -.0135818   .0236808    -0.57   0.566    -.0599969    .0328332
                    employed |  -.1215199   .0192729    -6.31   0.000    -.1592953   -.0837445
                      income |  -.0057881   .0038646    -1.50   0.134    -.0133628    .0017866
Yc4_restrictionsongatherings |   -.004115   .0095519    -0.43   0.667    -.0228369    .0146069
  Yc6_stayathomerequirements |   .0076355   .0082203     0.93   0.353    -.0084765    .0237475
                       _cons |   .6297358   .0310983    20.25   0.000     .5687823    .6906892
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     37906       37906           0    *|
        time |       284           1         283     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 1 TOP PANEL.xls", excel adjr2 lab dec(3) replace keep(vac_dem vac_ind vaccinated)
tables\Table 1 TOP PANEL.xls
dir : seeout

. reghdfe worn_mask vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restricti
> onsongatherings Yc6_stayathomerequirements [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 13973 singleton observations)
(MWFE estimator converged in 13 iterations)

HDFE Linear regression                            Number of obs   =    107,134
Absorbing 2 HDFE groups                           F(  11,  34820) =      27.28
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6375
                                                  Adj R-squared   =     0.4609
                                                  Within R-sq.    =     0.0129
Number of clusters (pid)     =     34,821         Root MSE        =     0.2912

                                               (Std. err. adjusted for 34,821 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                   worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |   .1700653   .0142373    11.95   0.000     .1421598    .1979708
                     vac_ind |   .1175461   .0163504     7.19   0.000     .0854988    .1495934
                  vaccinated |  -.0947802   .0143625    -6.60   0.000    -.1229311   -.0666294
                         dem |  -.0591876   .0164271    -3.60   0.000    -.0913853   -.0269899
                 indep_third |  -.0519747   .0141785    -3.67   0.000     -.079765   -.0241843
        ZLNpc_new_cases_7day |   .0360963   .0034802    10.37   0.000      .029275    .0429176
               out_workforce |   .0056604   .0210645     0.27   0.788    -.0356268    .0469476
                    employed |   .0188962    .016317     1.16   0.247    -.0130857    .0508781
                      income |   -.008225   .0033413    -2.46   0.014    -.0147741   -.0016759
Yc4_restrictionsongatherings |  -.0105159    .008506    -1.24   0.216    -.0271879    .0061561
  Yc6_stayathomerequirements |   .0175636   .0068183     2.58   0.010     .0041996    .0309277
                       _cons |   .8695959   .0279704    31.09   0.000      .814773    .9244188
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     34821       34821           0    *|
        time |       266           1         265     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 1 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated)
tables\Table 1 TOP PANEL.xls
dir : seeout

. reghdfe v_worry_ill vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restric
> tionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 14586 singleton observations)
(MWFE estimator converged in 13 iterations)

HDFE Linear regression                            Number of obs   =    102,270
Absorbing 2 HDFE groups                           F(  11,  33615) =      21.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6398
                                                  Adj R-squared   =     0.4613
                                                  Within R-sq.    =     0.0104
Number of clusters (pid)     =     33,616         Root MSE        =     0.2215

                                               (Std. err. adjusted for 33,616 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0898392   .0086906   -10.34   0.000    -.1068731   -.0728053
                     vac_ind |  -.0266292   .0090327    -2.95   0.003    -.0443336   -.0089249
                  vaccinated |  -.0167733   .0064449    -2.60   0.009    -.0294055   -.0041411
                         dem |   .0403107   .0110057     3.66   0.000     .0187391    .0618823
                 indep_third |  -.0001845   .0057367    -0.03   0.974    -.0114286    .0110596
        ZLNpc_new_cases_7day |   .0102439   .0025701     3.99   0.000     .0052064    .0152814
               out_workforce |  -.0573019   .0176879    -3.24   0.001    -.0919708   -.0226329
                    employed |  -.0368143   .0148702    -2.48   0.013    -.0659603   -.0076683
                      income |   -.000977   .0026973    -0.36   0.717    -.0062637    .0043098
Yc4_restrictionsongatherings |   .0016717   .0061464     0.27   0.786    -.0103754    .0137187
  Yc6_stayathomerequirements |   .0036762   .0054181     0.68   0.497    -.0069434    .0142958
                       _cons |   .1372071   .0230771     5.95   0.000     .0919752     .182439
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     33616       33616           0    *|
        time |       262           1         261     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 1 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated)
tables\Table 1 TOP PANEL.xls
dir : seeout

. reghdfe mostly_remote vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day income Yc4_restrictionsongatherings Yc6
> _stayathomerequirements  [aw=WEIGHT] if employed==1,  a(pid time) vce(cl pid)
(dropped 10794 singleton observations)
(MWFE estimator converged in 13 iterations)

HDFE Linear regression                            Number of obs   =     42,602
Absorbing 2 HDFE groups                           F(   9,  14925) =       4.35
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8051
                                                  Adj R-squared   =     0.6972
                                                  Within R-sq.    =     0.0032
Number of clusters (pid)     =     14,926         Root MSE        =     0.2729

                                               (Std. err. adjusted for 14,926 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0687783   .0190998    -3.60   0.000    -.1062163   -.0313403
                     vac_ind |  -.0522553   .0192214    -2.72   0.007    -.0899316    -.014579
                  vaccinated |  -.0003339   .0172036    -0.02   0.985     -.034055    .0333873
                         dem |   .0083057   .0219074     0.38   0.705    -.0346355     .051247
                 indep_third |  -.0066542   .0152849    -0.44   0.663    -.0366144     .023306
        ZLNpc_new_cases_7day |   .0009525   .0053428     0.18   0.859    -.0095199     .011425
                      income |    .002417    .004647     0.52   0.603    -.0066916    .0115256
Yc4_restrictionsongatherings |  -.0024699   .0111368    -0.22   0.824    -.0242994    .0193596
  Yc6_stayathomerequirements |    .003135   .0093595     0.33   0.738    -.0152108    .0214809
                       _cons |   .4283771   .0346791    12.35   0.000     .3604018    .4963523
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     14926       14926           0    *|
        time |       244           1         243     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 1 TOP PANEL.xls", excel adjr2 lab dec(4) keep(vac_dem vac_ind vaccinated)
tables\Table 1 TOP PANEL.xls
dir : seeout

. 
. **Lower panel
. //Estimate Stacked DID on ever and never treated
. 
. clear

. use "stacked_did_data_never_treated.dta"

. 
. label variable dem_vac "Vaccinated x Democrat"

. label variable ind_vac "Vaccinated x Independent"

. label variable vaccinated "Vaccinated"

. 
. gen _cohort_unit = st_unit

. gen _cohort_time = st_time

. gen _cohort = Cohort

. 
. *Note these lines below can take several minutes to run.
. 
. * Estimate Stacked DID
. stackdid Mostly_Isol dem_vac ind_vac vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restri
> ctionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  vce(cl _cohort_unit) nobuild tr(vaccinated) group(_cohort_unit) 
(dropped 122127 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =  4,760,433
Absorbing 2 HDFE groups                           F(  11,1553445) =     311.73
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6426
                                                  Adj R-squared   =     0.4667
                                                  Within R-sq.    =     0.0048
Number of clusters (_cohort_unit) =  1,553,446    Root MSE        =     0.3648

                                   (Std. err. adjusted for 1,553,446 clusters in _cohort_unit)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     dem_vac |  -.0375869   .0146027    -2.57   0.010    -.0662076   -.0089662
                     ind_vac |  -.0100604   .0157921    -0.64   0.524    -.0410124    .0208915
                  vaccinated |  -.0967218   .0120841    -8.00   0.000    -.1204062   -.0730374
                         dem |  -.0395707   .0033313   -11.88   0.000    -.0461001   -.0330414
                 indep_third |  -.0297906    .002034   -14.65   0.000    -.0337771    -.025804
        ZLNpc_new_cases_7day |   .0181669    .000696    26.10   0.000     .0168027    .0195311
               out_workforce |  -.0311963   .0042545    -7.33   0.000     -.039535   -.0228576
                    employed |  -.1306784   .0034123   -38.30   0.000    -.1373664   -.1239904
                      income |  -.0073579   .0007217   -10.19   0.000    -.0087725   -.0059433
Yc4_restrictionsongatherings |  -.0050702   .0016882    -3.00   0.003     -.008379   -.0017613
  Yc6_stayathomerequirements |   .0120859   .0014702     8.22   0.000     .0092044    .0149674
                       _cons |   .6373383   .0055386   115.07   0.000     .6264828    .6481938
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
 _cohort_time |     16583           1       16582     |
 _cohort_unit |   1553446     1553446           0    *|
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 1 LOWER PANEL.xls", excel adjr2 lab dec(3) replace keep(dem_vac ind_vac vaccinated)
tables\Table 1 LOWER PANEL.xls
dir : seeout

. stackdid worn_mask dem_vac ind_vac vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restrict
> ionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  vce(cl _cohort_unit) nobuild tr(vaccinated) group(_cohort_unit) 
(dropped 278084 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =  3,798,018
Absorbing 2 HDFE groups                           F(  11,1381580) =     417.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6906
                                                  Adj R-squared   =     0.5106
                                                  Within R-sq.    =     0.0083
Number of clusters (_cohort_unit) =  1,381,581    Root MSE        =     0.3093

                                   (Std. err. adjusted for 1,381,581 clusters in _cohort_unit)
----------------------------------------------------------------------------------------------
                             |               Robust
                   worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     dem_vac |   .1681238   .0140909    11.93   0.000     .1405061    .1957415
                     ind_vac |   .1214977   .0160563     7.57   0.000      .090028    .1529674
                  vaccinated |   -.066815   .0135807    -4.92   0.000    -.0934328   -.0401973
                         dem |  -.0410846   .0030076   -13.66   0.000    -.0469794   -.0351898
                 indep_third |   -.052474   .0023206   -22.61   0.000    -.0570223   -.0479257
        ZLNpc_new_cases_7day |    .038787   .0006712    57.79   0.000     .0374715    .0401024
               out_workforce |   .0237997   .0041894     5.68   0.000     .0155887    .0320107
                    employed |   .0376552   .0033951    11.09   0.000      .031001    .0443094
                      income |  -.0031621   .0006172    -5.12   0.000    -.0043718   -.0019525
Yc4_restrictionsongatherings |  -.0209537    .001758   -11.92   0.000    -.0243993    -.017508
  Yc6_stayathomerequirements |    .009004   .0013272     6.78   0.000     .0064027    .0116052
                       _cons |   .7561183   .0054844   137.87   0.000      .745369    .7668676
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
 _cohort_time |     15521           1       15520     |
 _cohort_unit |   1381581     1381581           0    *|
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 1 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(dem_vac ind_vac vaccinated)
tables\Table 1 LOWER PANEL.xls
dir : seeout

. stackdid v_worry_ill dem_vac ind_vac vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restri
> ctionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  vce(cl _cohort_unit) nobuild tr(vaccinated) group(_cohort_unit) 
(dropped 338329 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =  3,576,930
Absorbing 2 HDFE groups                           F(  11,1314661) =     123.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6942
                                                  Adj R-squared   =     0.5133
                                                  Within R-sq.    =     0.0029
Number of clusters (_cohort_unit) =  1,314,662    Root MSE        =     0.2017

                                   (Std. err. adjusted for 1,314,662 clusters in _cohort_unit)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     dem_vac |  -.0917111   .0085238   -10.76   0.000    -.1084174   -.0750047
                     ind_vac |  -.0274588   .0085747    -3.20   0.001     -.044265   -.0106526
                  vaccinated |  -.0228777   .0058189    -3.93   0.000    -.0342825   -.0114729
                         dem |   .0429354   .0020558    20.89   0.000     .0389061    .0469647
                 indep_third |  -.0006879   .0008192    -0.84   0.401    -.0022934    .0009176
        ZLNpc_new_cases_7day |   .0053274   .0003965    13.44   0.000     .0045504    .0061045
               out_workforce |   -.038267   .0033156   -11.54   0.000    -.0447654   -.0317687
                    employed |  -.0154578   .0029086    -5.31   0.000    -.0211587    -.009757
                      income |   -.004339   .0004562    -9.51   0.000    -.0052331   -.0034449
Yc4_restrictionsongatherings |   .0129253   .0010558    12.24   0.000      .010856    .0149947
  Yc6_stayathomerequirements |   .0114543    .000962    11.91   0.000     .0095688    .0133398
                       _cons |   .1107324   .0042217    26.23   0.000      .102458    .1190068
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
 _cohort_time |     15285           1       15284     |
 _cohort_unit |   1314662     1314662           0    *|
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 1 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(dem_vac ind_vac vaccinated)
tables\Table 1 LOWER PANEL.xls
dir : seeout

. stackdid mostly_remote dem_vac ind_vac vaccinated dem indep_third ZLNpc_new_cases_7day income Yc4_restrictionsongatherings Yc
> 6_stayathomerequirements if employed==1 [aw=WEIGHT],  vce(cl _cohort_unit) nobuild tr(vaccinated) group(_cohort_unit) 
(dropped 329894 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =  1,376,421
Absorbing 2 HDFE groups                           F(   9, 531357) =      31.44
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8259
                                                  Adj R-squared   =     0.7116
                                                  Within R-sq.    =     0.0010
Number of clusters (_cohort_unit) =    531,358    Root MSE        =     0.2643

                                     (Std. err. adjusted for 531,358 clusters in _cohort_unit)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     dem_vac |  -.0661628   .0186826    -3.54   0.000    -.1027801   -.0295455
                     ind_vac |  -.0518397    .018761    -2.76   0.006    -.0886107   -.0150687
                  vaccinated |  -.0104089   .0164227    -0.63   0.526    -.0425969    .0217791
                         dem |  -.0119293   .0043228    -2.76   0.006    -.0204019   -.0034568
                 indep_third |  -.0192711   .0024767    -7.78   0.000    -.0241253   -.0144168
        ZLNpc_new_cases_7day |   .0048836   .0009293     5.26   0.000     .0030622     .006705
                      income |   .0013233   .0008623     1.53   0.125    -.0003668    .0030134
Yc4_restrictionsongatherings |  -.0239594   .0020954   -11.43   0.000    -.0280663   -.0198524
  Yc6_stayathomerequirements |  -.0094214   .0016712    -5.64   0.000    -.0126968    -.006146
                       _cons |   .4342363   .0061892    70.16   0.000     .4221056    .4463669
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
 _cohort_time |     14162           1       14161     |
 _cohort_unit |    531358      531358           0    *|
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 1 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(dem_vac ind_vac vaccinated)
tables\Table 1 LOWER PANEL.xls
dir : seeout

. 
. 
. **************
. ** Table 2 ***
. **************
. 
. *Individual Approval of State Response
. 
. clear

. use "data_gallup.dta"

. 
. *GOP governors only
. reghdfe approvestate dem indep ZLNpc_new_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 
> age_group4 somecol ba grad live_w_children income if gopgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 5 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 2 HDFE groups                           F(  18,     25) =      79.47
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1598
                                                  Adj R-squared   =     0.1481
                                                  Within R-sq.    =     0.1110
Number of clusters (stateid) =         26         Root MSE        =     0.4074

                                       (Std. err. adjusted for 26 clusters in stateid)
--------------------------------------------------------------------------------------
                     |               Robust
approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |  -.2531698   .0554162    -4.57   0.000    -.3673017    -.139038
               indep |  -.1306318   .0574867    -2.27   0.032    -.2490279   -.0122357
ZLNpc_new_cases_7day |  -.0472893   .0167367    -2.83   0.009    -.0817592   -.0128195
            employed |    .133976   .0973648     1.38   0.181    -.0665504    .3345025
       out_workforce |   .1485348   .0939087     1.58   0.126    -.0448737    .3419434
                male |  -.0197117   .0217709    -0.91   0.374    -.0645498    .0251263
               Black |   .1168445   .0392253     2.98   0.006     .0360586    .1976305
                Hisp |    .044835    .027211     1.65   0.112     -.011207    .1008771
               Asian |   .3558646   .1354491     2.63   0.014      .076902    .6348272
             AmerInd |  -.2619356   .1456019    -1.80   0.084    -.5618084    .0379372
         Multiracial |  -.0368332   .1088146    -0.34   0.738    -.2609411    .1872747
               age10 |   .0419045   .0077149     5.43   0.000     .0260154    .0577935
          age_group4 |  -.0715401   .0308087    -2.32   0.029    -.1349917   -.0080884
             somecol |   .0021903   .0325374     0.07   0.947    -.0648217    .0692024
                  ba |   .0119962   .0446496     0.27   0.790    -.0799613    .1039538
                grad |  -.0311455   .0410463    -0.76   0.455    -.1156818    .0533909
     live_w_children |  -.0753312   .0184211    -4.09   0.000    -.1132701   -.0373923
              income |  -.0078088   .0068486    -1.14   0.265    -.0219138    .0062962
               _cons |   .5290586   .1013123     5.22   0.000     .3204021    .7377152
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        26          26           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 2.xls", excel adjr2 lab dec(3) replace keep(dem gop indep demrestrictionsongatherings goprestrict
> ionsongatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table 2.xls
dir : seeout

. 
. reghdfe approvestate  dem indep demrestrictionsongatherings Yc4_restrictionsongatherings indrestrictionsongatherings  ZLNpc_n
> ew_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_chil
> dren income ///
> if gopgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 2 HDFE groups                           F(  21,     25) =      67.99
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1665
                                                  Adj R-squared   =     0.1543
                                                  Within R-sq.    =     0.1181
Number of clusters (stateid) =         26         Root MSE        =     0.4059

                                               (Std. err. adjusted for 26 clusters in stateid)
----------------------------------------------------------------------------------------------
                             |               Robust
        approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   -.417561   .0629865    -6.63   0.000    -.5472841    -.287838
                       indep |  -.1121865   .0456398    -2.46   0.021    -.2061835   -.0181894
 demrestrictionsongatherings |   .1943836   .0797051     2.44   0.022     .0302279    .3585393
Yc4_restrictionsongatherings |  -.0476928     .07493    -0.64   0.530    -.2020139    .1066284
 indrestrictionsongatherings |  -.0269719    .075024    -0.36   0.722    -.1814867    .1275429
        ZLNpc_new_cases_7day |  -.0506705   .0167378    -3.03   0.006    -.0851426   -.0161984
                    employed |   .1229603   .1002248     1.23   0.231    -.0834566    .3293771
               out_workforce |   .1387839   .0953464     1.46   0.158    -.0575857    .3351536
                        male |  -.0229429   .0216356    -1.06   0.299    -.0675023    .0216164
                       Black |    .131036   .0411223     3.19   0.004     .0463431     .215729
                        Hisp |   .0434244   .0273435     1.59   0.125    -.0128906    .0997394
                       Asian |   .3614791   .1322453     2.73   0.011     .0891149    .6338433
                     AmerInd |  -.2652346   .1488177    -1.78   0.087    -.5717303    .0412611
                 Multiracial |  -.0415318   .1092195    -0.38   0.707    -.2664736      .18341
                       age10 |   .0431543   .0074725     5.78   0.000     .0277643    .0585442
                  age_group4 |  -.0724554   .0297807    -2.43   0.022      -.13379   -.0111208
                     somecol |   .0044732   .0323814     0.14   0.891    -.0622175    .0711639
                          ba |   .0127077   .0454275     0.28   0.782    -.0808519    .1062674
                        grad |  -.0281932   .0412325    -0.68   0.500    -.1131131    .0567266
             live_w_children |  -.0716748   .0193269    -3.71   0.001    -.1114793   -.0318704
                      income |  -.0076868   .0068194    -1.13   0.270    -.0217317    .0063581
                       _cons |   .5645088   .1033816     5.46   0.000     .3515904    .7774272
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        26          26           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 2.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionsonga
> therings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table 2.xls
dir : seeout

. 
. reghdfe approvestate  dem indep demstay Yc6_stayathome indstay ZLNpc_new_cases_7day employed out_workforce male  Black Hisp A
> sian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_children income ///
> if gopgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 2 HDFE groups                           F(  21,     25) =     112.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1625
                                                  Adj R-squared   =     0.1501
                                                  Within R-sq.    =     0.1138
Number of clusters (stateid) =         26         Root MSE        =     0.4069

                                             (Std. err. adjusted for 26 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       dem |  -.2073401   .0708529    -2.93   0.007    -.3532643   -.0614159
                     indep |  -.1013123   .0523986    -1.93   0.065    -.2092293    .0066047
 demstayathomerequirements |  -.0898998   .0764697    -1.18   0.251    -.2473921    .0675926
Yc6_stayathomerequirements |  -.0051538    .071111    -0.07   0.943    -.1516097    .1413021
 indstayathomerequirements |  -.0601355   .0893644    -0.67   0.507     -.244185     .123914
      ZLNpc_new_cases_7day |  -.0459324   .0172946    -2.66   0.014    -.0815513   -.0103136
                  employed |   .1330595   .0907577     1.47   0.155    -.0538595    .3199784
             out_workforce |   .1530036    .089972     1.70   0.101    -.0322973    .3383046
                      male |  -.0198799   .0220995    -0.90   0.377    -.0653946    .0256348
                     Black |   .1193279   .0391265     3.05   0.005     .0387454    .1999104
                      Hisp |   .0497785   .0288111     1.73   0.096    -.0095591    .1091161
                     Asian |    .362882   .1328548     2.73   0.011     .0892624    .6365015
                   AmerInd |  -.2650258   .1604642    -1.65   0.111    -.5955081    .0654565
               Multiracial |  -.0447153   .1065506    -0.42   0.678    -.2641604    .1747298
                     age10 |   .0412355   .0076257     5.41   0.000     .0255301    .0569409
                age_group4 |  -.0734843   .0307011    -2.39   0.025    -.1367144   -.0102541
                   somecol |   .0003876   .0320484     0.01   0.990    -.0656172    .0663924
                        ba |   .0099467   .0443334     0.22   0.824    -.0813596    .1012529
                      grad |  -.0308632   .0404838    -0.76   0.453     -.114241    .0525147
           live_w_children |  -.0733086   .0185042    -3.96   0.001    -.1114187   -.0351984
                    income |  -.0073098   .0070433    -1.04   0.309    -.0218158    .0071962
                     _cons |   .5330345   .0938217     5.68   0.000     .3398052    .7262639
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        26          26           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 2.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionsonga
> therings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table 2.xls
dir : seeout

. 
. *DEM governors only
. reghdfe approvestate gop indep ZLNpc_new_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 
> age_group4 somecol ba grad live_w_children income  if demgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  18,     23) =      47.46
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1313
                                                  Adj R-squared   =     0.1226
                                                  Within R-sq.    =     0.0887
Number of clusters (stateid) =         24         Root MSE        =     0.3873

                                       (Std. err. adjusted for 24 clusters in stateid)
--------------------------------------------------------------------------------------
                     |               Robust
approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 gop |  -.1977938   .0371345    -5.33   0.000    -.2746124   -.1209752
               indep |   -.117616   .0235349    -5.00   0.000    -.1663016   -.0689304
ZLNpc_new_cases_7day |   .0272277   .0143945     1.89   0.071    -.0025496     .057005
            employed |  -.0030539   .0427447    -0.07   0.944     -.091478    .0853701
       out_workforce |   .0366947   .0549307     0.67   0.511    -.0769381    .1503275
                male |  -.0678072   .0226303    -3.00   0.006    -.1146214   -.0209929
               Black |   -.009394   .0483581    -0.19   0.848    -.1094304    .0906424
                Hisp |    .043986   .0351794     1.25   0.224    -.0287882    .1167603
               Asian |   .1523258   .0310748     4.90   0.000     .0880426    .2166089
             AmerInd |   .1122449    .066694     1.68   0.106    -.0257221    .2502119
         Multiracial |  -.0397241   .0620222    -0.64   0.528    -.1680268    .0885785
               age10 |   .0254344   .0130264     1.95   0.063    -.0015128    .0523816
          age_group4 |   .0024981   .0571362     0.04   0.966    -.1156973    .1206934
             somecol |   .0419282   .0360724     1.16   0.257    -.0326932    .1165496
                  ba |   .0424452   .0285495     1.49   0.151    -.0166139    .1015044
                grad |   .1160485   .0340444     3.41   0.002     .0456224    .1864746
     live_w_children |  -.0053796   .0193051    -0.28   0.783    -.0453152     .034556
              income |    .001612   .0059532     0.27   0.789    -.0107032    .0139273
               _cons |   .7275114   .0830357     8.76   0.000     .5557389    .8992839
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 2.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionsonga
> therings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table 2.xls
dir : seeout

. 
. reghdfe approvestate  gop indep goprestrictionsongatherings indrestrictionsongatherings Yc4_restrictionsongatherings  ///
> ZLNpc_new_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live
> _w_children income ///
> if demgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  21,     23) =     676.26
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1347
                                                  Adj R-squared   =     0.1255
                                                  Within R-sq.    =     0.0922
Number of clusters (stateid) =         24         Root MSE        =     0.3866

                                               (Std. err. adjusted for 24 clusters in stateid)
----------------------------------------------------------------------------------------------
                             |               Robust
        approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         gop |  -.2504735   .0096364   -25.99   0.000    -.2704079   -.2305391
                       indep |  -.2713828   .0629804    -4.31   0.000    -.4016677    -.141098
 goprestrictionsongatherings |   .0568972   .0380374     1.50   0.148    -.0217892    .1355835
 indrestrictionsongatherings |   .1618585   .0703871     2.30   0.031     .0162517    .3074653
Yc4_restrictionsongatherings |    .055757   .0244211     2.28   0.032     .0052381    .1062759
        ZLNpc_new_cases_7day |   .0250736   .0138767     1.81   0.084    -.0036325    .0537798
                    employed |  -.0049236   .0438541    -0.11   0.912    -.0956427    .0857955
               out_workforce |   .0343352   .0552484     0.62   0.540    -.0799549    .1486253
                        male |  -.0685589   .0228077    -3.01   0.006    -.1157403   -.0213776
                       Black |   -.008888   .0487088    -0.18   0.857    -.1096499    .0918739
                        Hisp |   .0443175   .0353934     1.25   0.223    -.0288993    .1175342
                       Asian |   .1528843   .0286719     5.33   0.000     .0935719    .2121966
                     AmerInd |    .114795   .0681612     1.68   0.106    -.0262072    .2557971
                 Multiracial |   -.045748   .0628651    -0.73   0.474    -.1757944    .0842984
                       age10 |   .0267015   .0129484     2.06   0.051    -.0000844    .0534873
                  age_group4 |  -.0012187   .0545818    -0.02   0.982    -.1141298    .1116924
                     somecol |   .0411207   .0356744     1.15   0.261    -.0326775    .1149189
                          ba |   .0445821   .0275143     1.62   0.119    -.0123355    .1014997
                        grad |   .1155468   .0334385     3.46   0.002      .046374    .1847196
             live_w_children |  -.0049084   .0192091    -0.26   0.801    -.0446454    .0348286
                      income |   .0010629   .0060307     0.18   0.862    -.0114126    .0135384
                       _cons |   .6739512    .079216     8.51   0.000     .5100804    .8378221
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 2.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionsonga
> therings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table 2.xls
dir : seeout

. 
. reghdfe approvestate  gop indep  gopstay indstay Yc6_stayathome ///
> ZLNpc_new_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live
> _w_children income ///
> if demgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  21,     23) =      60.47
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1355
                                                  Adj R-squared   =     0.1263
                                                  Within R-sq.    =     0.0930
Number of clusters (stateid) =         24         Root MSE        =     0.3865

                                             (Std. err. adjusted for 24 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       gop |  -.1390802    .047646    -2.92   0.008    -.2376434   -.0405169
                     indep |  -.1195252   .0470359    -2.54   0.018    -.2168265   -.0222239
 gopstayathomerequirements |  -.1064382   .0540183    -1.97   0.061    -.2181836    .0053071
 indstayathomerequirements |    .003251   .0653042     0.05   0.961     -.131841     .138343
Yc6_stayathomerequirements |  -.0183116   .0398619    -0.46   0.650    -.1007722    .0641489
      ZLNpc_new_cases_7day |   .0290106    .014699     1.97   0.061    -.0013966    .0594177
                  employed |  -.0074478   .0444142    -0.17   0.868    -.0993256    .0844301
             out_workforce |    .032457   .0556331     0.58   0.565    -.0826289    .1475428
                      male |  -.0694535   .0218586    -3.18   0.004    -.1146714   -.0242356
                     Black |  -.0096012   .0487331    -0.20   0.846    -.1104133    .0912109
                      Hisp |   .0424424   .0352852     1.20   0.241    -.0305506    .1154355
                     Asian |   .1564022   .0301186     5.19   0.000     .0940972    .2187073
                   AmerInd |   .1115334   .0665665     1.68   0.107      -.02617    .2492367
               Multiracial |  -.0365188   .0619789    -0.59   0.561    -.1647318    .0916943
                     age10 |   .0244538   .0130684     1.87   0.074    -.0025803    .0514878
                age_group4 |   .0016005   .0583612     0.03   0.978    -.1191289      .12233
                   somecol |   .0389615   .0360308     1.08   0.291    -.0355738    .1134968
                        ba |   .0375941   .0288849     1.30   0.206    -.0221589    .0973472
                      grad |   .1107935   .0329032     3.37   0.003      .042728     .178859
           live_w_children |  -.0080212   .0189041    -0.42   0.675    -.0471273    .0310849
                    income |   .0020545   .0057929     0.35   0.726    -.0099289     .014038
                     _cons |   .7505903   .0927022     8.10   0.000     .5588212    .9423594
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table 2.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionsonga
> therings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table 2.xls
dir : seeout

. 
. 
. 
. *****************************
. *** SUPPLEMENTAL APPENDIX ***
. *****************************
. 
. *(note that S1, S4, and S8 are not tables or figures)
. 
. ****************
. *** Table S2 ***
. ****************
. 
. *Distribution of Survey Participation by Number of Responses per Individual
. 
. clear

. use "data_gallup.dta"

. 
. egen uni=tag(pid)

. total uni

Total estimation                       Number of obs = 164,327

--------------------------------------------------------------
             |      Total   Std. err.     [95% conf. interval]
-------------+------------------------------------------------
         uni |      54216   190.6013      53842.43    54589.57
--------------------------------------------------------------

. sum pid uni

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
         pid |    164,327    27135.39    15356.85          1      54216
         uni |    164,327    .3299275    .4701879          0          1

. bysort pid: egen interviews = count(month)

. collapse (count) Observations = uni, by(interviews)

. rename interviews Number_of_responses

. su Observations, meanonly

. gen Percent = round(100 * Observations / r(sum), 0.01)

. tostring Number_of_responses, replace force
Number_of_responses was float now str2

. su Observations, meanonly

. local total_obs = r(sum)

. expand 2 if _n == 1
(1 observation created)

. replace Number_of_responses = "Total" if _n == _N
variable Number_of_responses was str2 now str5
(1 real change made)

. replace Observations = `total_obs' if _n == _N
(1 real change made)

. replace Percent = 100 if _n == _N
(1 real change made)

. 
. export excel using "tables\Table S2.xls", firstrow(variables) replace
file tables\Table S2.xls saved

. 
. 
. *****************
. *** Figure S3 ***
. *****************
. 
. *Full and partial vaccination status by party by month
. 
. clear

. use "data_gallup.dta"

. 
. keep if gop==1 | dem==1
(50,335 observations deleted)

. egen year_month=concat(year month), punc(-)

. 
. sort time gop

. collapse (first) time  time_string (min) min_time=time (max) max_time=time ///
> (mean) vaccinated fullvac [aw=WEIGHT], by(year_month gop)

. 
. keep time  year_month gop vaccinated fullvac

. sort gop time

. 
. foreach x in vaccinated  fullvac {
  2. egen min_`x'=min(time) if `x'!=.
  3. egen max_`x'=max(min_`x')
  4. }

. 
. sort gop time 

. 
. gen time_string=time

. format time_string %td

. 
. sort gop time 

. 
. twoway  line  vaccinated time_string if time>22264 & gop==0,  connect(direct) lcolor(blue)  ///
> || line  vaccinated time_string if time>22264 & gop==1,  connect(direct) lcolor(red*.6)  lpattern(longdash) ///
> ||  line  fullvac time_string if time>22264 & gop==0,  connect(direct) lcolor(blue) lpattern(dash_dot) ///
> || line  fullvac time_string if time>22264 & gop==1,  connect(direct) lcolor(red*.6)  lpattern(shortdash) ///
> ytitle("") ///
> xtitle("") xlabel(22264(60)22508, grid gmax labgap(tiny)) ///
> xline(22325 22354 22389 , lwidth(.5in) lc(gray*.2)) ///
> xline(22325 22389, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> plotregion(color(white)) graphregion(color(white)) ///
> legend(label(2 "Republican: any vaccination") label(1 "Democrat: any vaccination") label(3 "Democrat: fully") label(4 "Republ
> ican: fully")  rows(2) pos(6)) ///
> title("Vaccination status by party identification", span) 

. graph export "figures/Figure S3.png", replace
file figures/Figure S3.png saved as PNG format

. 
. 
. 
. ****************
. *** Table S5 ***
. ****************
. 
. *Descriptive Statistics 
. 
. clear

. use "data_gallup.dta"

. 
. label variable dem "Democrat"

. label variable gop "Republican"

. label variable indep_third "Independent (or third party)"

. label variable Yc6_stayathomerequirements "Stay-at-home-order"

. label variable vaccinated "Vaccination status"

. 
. estpost summarize Mostly_Isol worn_mask v_worry_ill mostly_remote ///
> dem indep_third gop ///
> LNpc_new_cases_7day ZLNpc_new_cases_7day employed out_workforce live_w_children income ///
> male age10 age_group4 somecol ba grad AmerInd Asian Black Hisp Multiracial ///
> Y3h6_facialcoverings Yc4_restrictionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing vaccinated [aw=WEIGHT]

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max)     e(sum) 
-------------+----------------------------------------------------------------------------------------
 Mostly_Isol |    158437   158410.8   .5002876   .2500015   .5000015          0          1   79250.95 
   worn_mask |    133820     133828   .8041518   .1574929   .3968537          0          1     107618 
 v_worry_ill |    129104   129149.8   .1027973   .0922308   .3036952          0          1   13276.25 
mostly_rem~e |     55861   65382.98   .4395437   .2463494    .496336          0          1   28738.68 
         dem |    155263   155247.6   .4157496   .2429034   .4928523          0          1   64544.14 
 indep_third |    155263   155247.6   .2825711    .202726    .450251          0          1    43868.5 
         gop |    155263   155247.6   .3016793   .2106703   .4589883          0          1      46835 
LNpc_new_c~y |    163916   163869.3   3.947101   2.715384   1.647842          0   9.106579   646808.6 
ZLNpc_new_~y |    163916   163869.3   .0119239   1.013757   1.006855  -2.399811   3.164438   1953.968 
    employed |    163460   163509.6   .5977584   .2404448   .4903517          0          1   97739.21 
out_workfo~e |    158204   156779.5   .3304758    .221263    .470386          0          1   51811.85 
live_w_chi~n |    163076   162592.9   .3152524   .2158696   .4646177          0          1   51257.81 
      income |    156584     158819   5.916478    4.93053    2.22048          1         10   939649.2 
        male |    164327   164326.7   .4843894   .2497578   .4997578          0          1   79598.13 
       age10 |    164327   164326.7   5.040506   2.736577    1.65426        1.8         12     828290 
  age_group4 |    164326   164325.4   .2408357    .182835   .4275921          0          1   39575.42 
     somecol |    162556   163192.9   .2962479   .2084864   .4566031          0          1   48345.57 
          ba |    162556   163192.9   .1529306   .1295436   .3599217          0          1   24957.19 
        grad |    162556   163192.9    .178328    .146528   .3827898          0          1   29101.87 
     AmerInd |    163732   163917.3   .0041426   .0041254   .0642296          0          1   679.0403 
       Asian |    163732   163917.3   .0056371   .0056054   .0748691          0          1   924.0223 
       Black |    163732   163917.3   .1134219    .100558   .3171088          0          1   18591.81 
        Hisp |    163732   163917.3   .1528041   .1294558   .3597996          0          1   25047.22 
 Multiracial |    163732   163917.3   .0188582   .0185026   .1360244          0          1   3091.179 
Y3h6_facia~s |    163636   163314.8   .3976177   .2395193   .4894071          0          1   64936.86 
Yc4_restri~s |    163649   163327.2   .8188478    .148337   .3851454          0          1   133740.2 
Yc6_stayat~s |    163649   163327.2   .3632875   .2313111   .4809481          0          1   59334.75 
Yc2_workpl~g |    163649   163327.2   .6685218   .2216018    .470746          0          1   109187.8 
  vaccinated |    164063   164071.1   .1075789   .0960062   .3098487          0          1   17650.58 

. 
. esttab using "tables\Table S5.csv", label cells("count mean(fmt(2)) sd(fmt(2))") replace nonumber noobs
(output written to tables\Table S5.csv)

. 
. *Skewness of COVID cases - as per notes of Table S5 
. clear

. use "COVID_data_from_USA_Facts.dta"

. 
. * Skewness of covid cases
. sum pc_new_cases_7day, detail

                  (mean) pc_new_cases_7day
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0      -19182.88
 5%            0      -13312.03
10%            0      -13312.03       Obs           2,227,678
25%     21.60637      -13312.03       Sum of wgt.   2,227,678

50%     116.1235                      Mean           237.4271
                        Largest       Std. dev.      378.6822
75%     333.3535       70061.52
90%     642.5707       70574.16       Variance       143400.2
95%     859.0456       70574.16       Skewness       23.43283
99%     1424.121        71086.8       Kurtosis         3833.7

. 
. * Skewness of covid cases - logged
. gen ln_pc_new_cases=log(pc_new_cases_7day+1)
(19,556 missing values generated)

. sum ln_pc_new_cases, detail

                       ln_pc_new_cases
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0      -4.683256
 5%            0      -3.040045
10%            0      -3.040045       Obs           2,213,394
25%     3.176738      -2.795824       Sum of wgt.   2,213,394

50%     4.777658                      Mean           4.161098
                        Largest       Std. dev.      2.205502
75%      5.81882       11.15714
90%     6.470405       11.16443       Variance       4.864238
95%     6.759255       11.16443       Skewness       -.829886
99%      7.26402       11.17167       Kurtosis       2.531808

. 
. 
. ****************
. *** Table S6 ***
. ****************
. 
. *Descriptive Statistics of Individual-level COVID-19 Responses by Party
. 
. clear

. use "data_gallup.dta"

. 
. estpost summarize Mostly_Isol worn_mask v_worry_ill mostly_remote approve [aw=WEIGHT] if dem==1

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max)     e(sum) 
-------------+----------------------------------------------------------------------------------------
 Mostly_Isol |     64469   64441.37   .6058154   .2388068   .4886786          0          1   39039.57 
   worn_mask |     55266   55258.59   .9220578   .0718685   .2680831          0          1   50951.62 
 v_worry_ill |     53264   53223.64   .1601144   .1344803   .3667156          0          1   8521.872 
mostly_rem~e |     22804   27561.15   .5747865   .2444177   .4943862          0          1   15841.78 
approvesta~e |      4195   4233.821   .7790648   .1721639   .4149264          0          1   3298.421 

. estimates store dems

. 
. estpost summarize Mostly_Isol worn_mask v_worry_ill mostly_remote approve [aw=WEIGHT] if gop==1

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max)     e(sum) 
-------------+----------------------------------------------------------------------------------------
 Mostly_Isol |     49312   46737.21   .3742491   .2341915   .4839333          0          1   17491.36 
   worn_mask |     41666   39595.31   .6633999   .2233058   .4725525          0          1   26267.53 
 v_worry_ill |     40039   38017.75   .0367395   .0353906    .188124          0          1   1396.755 
mostly_rem~e |     15929   17096.55   .2780843    .200766   .4480692          0          1   4754.284 
approvesta~e |      3403   3117.317   .7714441   .1763699   .4199642          0          1   2404.836 

. estimates store reps

. 
. estpost summarize Mostly_Isol worn_mask v_worry_ill mostly_remote approve [aw=WEIGHT] if indep_third==1

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max)     e(sum) 
-------------+----------------------------------------------------------------------------------------
 Mostly_Isol |     41176   43772.89   .4789169   .2495616   .4995614          0          1   20963.58 
   worn_mask |     35912   37981.86   .7797642   .1717368   .4144114          0          1    29616.9 
 v_worry_ill |     34854   36932.35   .0891865   .0812346   .2850168          0          1   3293.866 
mostly_rem~e |     16763   20378.47   .3924764   .2384529   .4883164          0          1    7998.07 
approvesta~e |      2486   2788.485   .7177959   .2026464   .4501627          0          1   2001.563 

. estimates store inds

. 
. esttab dems reps inds using "tables\Table S6.csv", label ///
>     cells("count mean(fmt(2))  sd(fmt(2))") replace ///
>     nonumber noobs ///
>     mtitles("Democrats" "Republicans" "Independents")
(output written to tables\Table S6.csv)

. 
. 
. ****************
. *** Table S7 ***
. ****************
. 
. *Comparison of Demographic Descriptive Statistics across Samples
. 
. bysort pid: egen interviews = count(month)

. 
. local vars employed out_workforce live_w_children income ///
> male age10 age_group4 somecol ba grad Black Hisp Asian AmerInd Multiracia

. estpost summarize `vars' [aw=WEIGHT]

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max)     e(sum) 
-------------+----------------------------------------------------------------------------------------
    employed |    163460   163509.6   .5977584   .2404448   .4903517          0          1   97739.21 
out_workfo~e |    158204   156779.5   .3304758    .221263    .470386          0          1   51811.85 
live_w_chi~n |    163076   162592.9   .3152524   .2158696   .4646177          0          1   51257.81 
      income |    156584     158819   5.916478    4.93053    2.22048          1         10   939649.2 
        male |    164327   164326.7   .4843894   .2497578   .4997578          0          1   79598.13 
       age10 |    164327   164326.7   5.040506   2.736577    1.65426        1.8         12     828290 
  age_group4 |    164326   164325.4   .2408357    .182835   .4275921          0          1   39575.42 
     somecol |    162556   163192.9   .2962479   .2084864   .4566031          0          1   48345.57 
          ba |    162556   163192.9   .1529306   .1295436   .3599217          0          1   24957.19 
        grad |    162556   163192.9    .178328    .146528   .3827898          0          1   29101.87 
       Black |    163732   163917.3   .1134219    .100558   .3171088          0          1   18591.81 
        Hisp |    163732   163917.3   .1528041   .1294558   .3597996          0          1   25047.22 
       Asian |    163732   163917.3   .0056371   .0056054   .0748691          0          1   924.0223 
     AmerInd |    163732   163917.3   .0041426   .0041254   .0642296          0          1   679.0403 
 Multiracial |    163732   163917.3   .0188582   .0185026   .1360244          0          1   3091.179 

. estimates store full

. 
. estpost summarize `vars' [aw=WEIGHT] if interviews > 1

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max)     e(sum) 
-------------+----------------------------------------------------------------------------------------
    employed |    151584   149622.7   .5917362   .2415861   .4915141          0          1   88537.14 
out_workfo~e |    146785   143639.4   .3404201   .2245358   .4738521          0          1   48897.73 
live_w_chi~n |    151837   149540.5    .310121   .2139474   .4625444          0          1   46375.66 
      income |    145177   145320.4   5.933582   4.858062   2.204101          1         10   862270.5 
        male |    152373   150379.9   .4801383   .2496071    .499607          0          1   72203.15 
       age10 |    152373   150379.9   5.094648    2.72316     1.6502        1.8       10.6   766132.6 
  age_group4 |    152373   150379.9   .2504581   .1877301   .4332783          0          1   37663.86 
     somecol |    150809   149393.5   .2909043   .2062804    .454181          0          1   43459.22 
          ba |    150809   149393.5   .1491868   .1269309   .3562737          0          1   22287.54 
        grad |    150809   149393.5   .1799572   .1475736   .3841531          0          1   26884.45 
       Black |    151850   150020.3   .1105134   .0983008   .3135296          0          1   16579.25 
        Hisp |    151850   150020.3   .1523311   .1291272   .3593427          0          1   22852.76 
       Asian |    151850   150020.3   .0050893   .0050634   .0711576          0          1   763.4949 
     AmerInd |    151850   150020.3    .003958   .0039424   .0627882          0          1   593.7798 
 Multiracial |    151850   150020.3   .0182222   .0178903   .1337545          0          1   2733.701 

. estimates store nosingletons

. 
. esttab full nosingletons using "tables\Table S7.csv", label ///
>     cells("mean(fmt(2))") replace ///
>     nonumber noobs ///
>     mtitles("Full sample" "Mean excluding singleton responses")
(output written to tables\Table S7.csv)

. 
. 
. ****************
. *** Table S9 ***
. ****************
. 
. *Parameter Estimates for Figure 2. Table created together with Figure 2 -see above
. 
. 
. ******************
. *** Figure S10 ***
. ******************
. 
. *Change in Partisan Gap in COVID-19 Responses, Excluding Party-Switchers
. *note that in regressions with individual fixed effects for non-party switchers, main effects of party not included (and woul
> d drop out) because party switchers not included
. 
. clear

. use "data_gallup.dta"

. 
. keep if partyswitch==0
(42,875 observations deleted)

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(3,020 real changes made)
(2,728 real changes made)
(2,719 real changes made)
(2,569 real changes made)
(2,487 real changes made)
(3,433 real changes made)
(2,473 real changes made)
(2,475 real changes made)
(2,820 real changes made)

. egen minmonthvac=min(month_number) if vaccinated!=., by(pid)
(176 missing values generated)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(22,436 missing values generated)

. egen minmonthisol=min(month_number) if Mostly_Isol!=., by(pid)
(3,996 missing values generated)

. egen minmonthworry=min(month_number) if v_worry_ill!=., by(pid)
(25,858 missing values generated)

. egen minmonthmostly_remote=min(month_number) if mostly_remote!=., by(pid)
(80,540 missing values generated)

. 
. global controls_fe_model "ZLNpc_new_cases_7day out_workforce employed income"

. global controls_main_model "male age10 age_group4 live_w_children  somecol ba grad AmerInd Asian Black Hisp Multiracial"

. 
. *Mostly Isolate
. 
. estimates clear

. reghdfe Mostly_Isol  dmonthdum3-dmonthdum20 imonthdum3-imonthdum20  Yc4_restrictionsongatherings Yc6_stayathomerequirements $
> controls_fe_model [aw=WEIGHT]  if minmonthisol==3 ,  a(time pid) vce(cl ctyfip)
(dropped 400 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     44,181
Absorbing 2 HDFE groups                           F(  42,   1787) =       3.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5916
                                                  Adj R-squared   =     0.4343
                                                  Within R-sq.    =     0.0146
Number of clusters (ctyfip)  =      1,788         Root MSE        =     0.3755

                                             (Std. err. adjusted for 1,788 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum3 |   .1040345   .0285678     3.64   0.000     .0480047    .1600642
                  dmonthdum4 |   .1928691   .0340736     5.66   0.000     .1260409    .2596973
                  dmonthdum5 |   .1702233   .0362182     4.70   0.000     .0991889    .2412577
                  dmonthdum6 |   .1772182   .0371519     4.77   0.000     .1043526    .2500839
                  dmonthdum7 |    .241569    .042073     5.74   0.000     .1590515    .3240865
                  dmonthdum8 |   .1909469   .0844141     2.26   0.024     .0253862    .3565077
                  dmonthdum9 |   .2325556   .0732014     3.18   0.002     .0889863     .376125
                 dmonthdum10 |   .1082062   .0876086     1.24   0.217    -.0636199    .2800323
                 dmonthdum11 |   .1506463   .0436373     3.45   0.001     .0650607    .2362318
                 dmonthdum12 |   .2366047   .0409705     5.78   0.000     .1562496    .3169597
                 dmonthdum13 |    .133654    .046828     2.85   0.004     .0418106    .2254975
                 dmonthdum14 |   .2504107   .0468741     5.34   0.000     .1584768    .3423446
                 dmonthdum15 |   .0751835   .0559892     1.34   0.180    -.0346277    .1849946
                 dmonthdum16 |   .1123317   .0516966     2.17   0.030     .0109396    .2137238
                 dmonthdum17 |   .0410964    .046136     0.89   0.373    -.0493897    .1315825
                 dmonthdum18 |   .0190912    .052645     0.36   0.717    -.0841611    .1223434
                 dmonthdum19 |   .1908276   .0527344     3.62   0.000        .0874    .2942552
                 dmonthdum20 |   .0058081   .0517458     0.11   0.911    -.0956806    .1072968
                  imonthdum3 |    .044931   .0360154     1.25   0.212    -.0257057    .1155677
                  imonthdum4 |   .1517548   .0398059     3.81   0.000     .0736837    .2298259
                  imonthdum5 |   .0958372   .0411698     2.33   0.020     .0150911    .1765833
                  imonthdum6 |   .1423885   .0427418     3.33   0.001     .0585594    .2262176
                  imonthdum7 |   .1659055   .0477096     3.48   0.001     .0723331    .2594779
                  imonthdum8 |   .1746604   .0992061     1.76   0.078    -.0199118    .3692326
                  imonthdum9 |   .3218033   .0800694     4.02   0.000     .1647637    .4788429
                 imonthdum10 |  -.0392695   .1014161    -0.39   0.699    -.2381761    .1596371
                 imonthdum11 |   .1168482   .0671193     1.74   0.082    -.0147923    .2484888
                 imonthdum12 |   .1222427   .0463194     2.64   0.008     .0313968    .2130887
                 imonthdum13 |   .1492719      .0541     2.76   0.006     .0431659    .2553778
                 imonthdum14 |   .2054595   .0630307     3.26   0.001     .0818379    .3290811
                 imonthdum15 |    .084059   .0732844     1.15   0.252    -.0596732    .2277912
                 imonthdum16 |   .0875144   .0612173     1.43   0.153    -.0325505    .2075794
                 imonthdum17 |   .1131164   .0513725     2.20   0.028       .01236    .2138728
                 imonthdum18 |   .0781004   .0708029     1.10   0.270    -.0607648    .2169657
                 imonthdum19 |   .2680964   .0658326     4.07   0.000     .1389795    .3972134
                 imonthdum20 |   .0070735   .0495454     0.14   0.886    -.0900994    .1042465
Yc4_restrictionsongatherings |   .0014228   .0167732     0.08   0.932    -.0314743    .0343198
  Yc6_stayathomerequirements |   .0217833   .0132949     1.64   0.102     -.004292    .0478586
        ZLNpc_new_cases_7day |   .0189994   .0065333     2.91   0.004     .0061857    .0318132
               out_workforce |   .0171647   .0455236     0.38   0.706    -.0721204    .1064498
                    employed |    -.05431   .0353216    -1.54   0.124     -.123586     .014966
                      income |   .0005427    .007928     0.07   0.945    -.0150064    .0160919
                       _cons |   .4680709   .0654443     7.15   0.000     .3397154    .5964264
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       271           1         270     |
         pid |     11978       11978           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe Mostly_Isol dem indep_third dmonthdum3-dmonthdum20 imonthdum3-imonthdum20 Yc4_restrictionsongatherings Yc6_stayathome
> requirements $controls_main_model $controls_fe_model  [aw=WEIGHT],  a(time ctyfip) vce(cl ctyfip)
(dropped 17 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =    103,815
Absorbing 2 HDFE groups                           F(  56,   2381) =      40.49
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2746
                                                  Adj R-squared   =     0.2550
                                                  Within R-sq.    =     0.0733
Number of clusters (ctyfip)  =      2,382         Root MSE        =     0.4315

                                             (Std. err. adjusted for 2,382 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .0734176   .0225523     3.26   0.001     .0291935    .1176418
                 indep_third |   .0476037   .0244396     1.95   0.052    -.0003214    .0955289
                  dmonthdum3 |   .0708122   .0236082     3.00   0.003     .0245174    .1171069
                  dmonthdum4 |   .1870256    .028432     6.58   0.000     .1312715    .2427797
                  dmonthdum5 |   .1799298   .0287742     6.25   0.000     .1235047    .2363549
                  dmonthdum6 |   .2134928   .0297058     7.19   0.000      .155241    .2717447
                  dmonthdum7 |   .2061466   .0310196     6.65   0.000     .1453184    .2669748
                  dmonthdum8 |   .2348045   .0480921     4.88   0.000     .1404978    .3291111
                  dmonthdum9 |   .1731985   .0493947     3.51   0.000     .0763374    .2700595
                 dmonthdum10 |   .2054059   .0518569     3.96   0.000     .1037166    .3070952
                 dmonthdum11 |   .2274698   .0347683     6.54   0.000     .1592905    .2956491
                 dmonthdum12 |   .2054009   .0294695     6.97   0.000     .1476123    .2631895
                 dmonthdum13 |   .2110331   .0331868     6.36   0.000      .145955    .2761111
                 dmonthdum14 |   .2354607   .0307712     7.65   0.000     .1751196    .2958018
                 dmonthdum15 |   .0869713   .0320798     2.71   0.007      .024064    .1498786
                 dmonthdum16 |    .067018   .0306258     2.19   0.029     .0069619     .127074
                 dmonthdum17 |    .045822     .02955     1.55   0.121    -.0121244    .1037684
                 dmonthdum18 |  -.0146357   .0311672    -0.47   0.639    -.0757533     .046482
                 dmonthdum19 |   .0826423   .0322569     2.56   0.010     .0193878    .1458968
                 dmonthdum20 |   .0606586   .0312846     1.94   0.053    -.0006894    .1220065
                  imonthdum3 |   .0285665   .0273901     1.04   0.297    -.0251445    .0822774
                  imonthdum4 |   .1065807   .0305894     3.48   0.001     .0465961    .1665653
                  imonthdum5 |   .0967026   .0327178     2.96   0.003     .0325443    .1608609
                  imonthdum6 |   .1385653   .0320299     4.33   0.000      .075756    .2013746
                  imonthdum7 |   .1483607   .0369648     4.01   0.000     .0758742    .2208472
                  imonthdum8 |   .1805924   .0601467     3.00   0.003     .0626471    .2985377
                  imonthdum9 |   .1884106   .0613459     3.07   0.002     .0681138    .3087074
                 imonthdum10 |   .0401814   .0651283     0.62   0.537    -.0875327    .1678956
                 imonthdum11 |   .2113981    .041307     5.12   0.000     .1303967    .2923995
                 imonthdum12 |   .1004023    .037363     2.69   0.007     .0271349    .1736696
                 imonthdum13 |   .1520124    .040675     3.74   0.000     .0722504    .2317745
                 imonthdum14 |   .1593591   .0382031     4.17   0.000     .0844442    .2342739
                 imonthdum15 |   .1197924    .038347     3.12   0.002     .0445955    .1949893
                 imonthdum16 |   .0663965   .0351203     1.89   0.059    -.0024731    .1352661
                 imonthdum17 |   .0787754   .0316689     2.49   0.013      .016674    .1408768
                 imonthdum18 |   .0517079   .0369159     1.40   0.161    -.0206828    .1240985
                 imonthdum19 |   .0906403     .03894     2.33   0.020     .0142805    .1670001
                 imonthdum20 |     .05423   .0336093     1.61   0.107    -.0116765    .1201366
Yc4_restrictionsongatherings |  -.0115566   .0113095    -1.02   0.307    -.0337341    .0106209
  Yc6_stayathomerequirements |   .0139211   .0091722     1.52   0.129    -.0040653    .0319075
                        male |  -.0385749   .0078568    -4.91   0.000    -.0539818    -.023168
                       age10 |  -.0171154   .0035062    -4.88   0.000    -.0239909   -.0102399
                  age_group4 |   .0204428   .0128951     1.59   0.113     -.004844    .0457297
             live_w_children |  -.0432348    .008518    -5.08   0.000    -.0599382   -.0265313
                     somecol |   .0157693   .0099973     1.58   0.115    -.0038349    .0353736
                          ba |   .0772853   .0123389     6.26   0.000     .0530892    .1014814
                        grad |   .0939988   .0118427     7.94   0.000     .0707758    .1172218
                     AmerInd |  -.0745535   .0502902    -1.48   0.138    -.1731706    .0240635
                       Asian |   .0473725   .0374339     1.27   0.206    -.0260338    .1207789
                       Black |  -.0437838   .0140398    -3.12   0.002    -.0713153   -.0162522
                        Hisp |   .0078478    .013981     0.56   0.575    -.0195685    .0352641
                 Multiracial |  -.0536315   .0221526    -2.42   0.016    -.0970719   -.0101912
        ZLNpc_new_cases_7day |   .0194576   .0042493     4.58   0.000      .011125    .0277903
               out_workforce |   .0024032   .0162933     0.15   0.883    -.0295473    .0343536
                    employed |  -.1717071   .0147048   -11.68   0.000    -.2005428   -.1428715
                      income |   .0060977   .0018468     3.30   0.001     .0024762    .0097192
                       _cons |   .5336292   .0268311    19.89   0.000     .4810145    .5862439
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       287           1         286     |
      ctyfip |      2382        2382           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("MostlyIsolate", replace) ///
> title("Mostly Isolating (base month March 2020)") xtitle("Pandemic Month")
(file MostlyIsolate.gph not found)
file MostlyIsolate.gph saved

. 
. *Worn Masks
. 
. estimates clear

. reghdfe worn_mask dmonthdum4-dmonthdum20 imonthdum4-imonthdum20  $controls_fe_model  Y3h6_facialcoverings [aw=WEIGHT]  if min
> monthmask==4  , a(time pid) vce(cl ctyfip)
(dropped 1360 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     52,975
Absorbing 2 HDFE groups                           F(  39,   2005) =       7.29
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6297
                                                  Adj R-squared   =     0.4517
                                                  Within R-sq.    =     0.0224
Number of clusters (ctyfip)  =      2,006         Root MSE        =     0.2988

                                     (Std. err. adjusted for 2,006 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
          dmonthdum4 |   .0470126   .0313223     1.50   0.134    -.0144149    .1084402
          dmonthdum5 |   .0750992   .0272657     2.75   0.006     .0216271    .1285714
          dmonthdum6 |  -.0331415   .0241925    -1.37   0.171    -.0805865    .0143035
          dmonthdum7 |  -.0707839   .0255985    -2.77   0.006    -.1209863   -.0205816
          dmonthdum8 |  -.0720462   .0437099    -1.65   0.099    -.1577678    .0136755
          dmonthdum9 |  -.0403286   .0479866    -0.84   0.401    -.1344374    .0537801
         dmonthdum10 |    -.04264   .0368147    -1.16   0.247    -.1148391    .0295591
         dmonthdum11 |  -.0086209    .030844    -0.28   0.780    -.0691104    .0518687
         dmonthdum12 |  -.1066757   .0297622    -3.58   0.000    -.1650439   -.0483076
         dmonthdum13 |  -.0248555   .0331876    -0.75   0.454    -.0899412    .0402303
         dmonthdum14 |  -.0653162   .0321754    -2.03   0.042    -.1284169   -.0022154
         dmonthdum15 |  -.0071885   .0376899    -0.19   0.849     -.081104     .066727
         dmonthdum16 |   .0873025   .0405501     2.15   0.031     .0077777    .1668274
         dmonthdum17 |   .1917548    .036897     5.20   0.000     .1193944    .2641153
         dmonthdum18 |   .1874156   .0500034     3.75   0.000     .0893515    .2854796
         dmonthdum19 |   .2136469   .0421327     5.07   0.000     .1310184    .2962755
         dmonthdum20 |   .2044766   .0343214     5.96   0.000     .1371671     .271786
          imonthdum4 |   .0558415   .0374552     1.49   0.136    -.0176136    .1292966
          imonthdum5 |   .0520242   .0312938     1.66   0.097    -.0093477     .113396
          imonthdum6 |   .0229249   .0290833     0.79   0.431    -.0341117    .0799615
          imonthdum7 |  -.0089876   .0311613    -0.29   0.773    -.0700996    .0521244
          imonthdum8 |  -.0402797   .0481287    -0.84   0.403    -.1346673    .0541079
          imonthdum9 |  -.0882848   .0581692    -1.52   0.129    -.2023633    .0257937
         imonthdum10 |   .0599032   .0516174     1.16   0.246    -.0413261    .1611326
         imonthdum11 |   .0935049   .0407295     2.30   0.022     .0136283    .1733814
         imonthdum12 |  -.0336219   .0346383    -0.97   0.332    -.1015529     .034309
         imonthdum13 |   .0336992   .0395042     0.85   0.394    -.0437743    .1111727
         imonthdum14 |   .0039239   .0366739     0.11   0.915     -.067999    .0758467
         imonthdum15 |   .0629921   .0434276     1.45   0.147    -.0221758      .14816
         imonthdum16 |   .0568551   .0470454     1.21   0.227    -.0354078    .1491181
         imonthdum17 |   .1152128   .0481487     2.39   0.017     .0207861    .2096396
         imonthdum18 |   .0619911   .0619599     1.00   0.317    -.0595215    .1835037
         imonthdum19 |   .0577693   .0542925     1.06   0.287    -.0487063    .1642448
         imonthdum20 |   .1017333   .0480814     2.12   0.034     .0074385     .196028
ZLNpc_new_cases_7day |   .0395555   .0054903     7.20   0.000     .0287882    .0503227
       out_workforce |   .0094528   .0316999     0.30   0.766    -.0527155     .071621
            employed |   .0112965   .0261064     0.43   0.665    -.0399019     .062495
              income |  -.0061375   .0051684    -1.19   0.235    -.0162734    .0039984
Y3h6_facialcoverings |   .0127123   .0102229     1.24   0.214    -.0073363    .0327609
               _cons |   .7964591   .0401104    19.86   0.000     .7177966    .8751216
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       266           1         265     |
         pid |     16900       16900           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 
. estimates store fes

. reghdfe worn_mask dem indep_third dmonthdum4-dmonthdum20 imonthdum4-imonthdum20 $controls_fe_model  Y3h6_facialcoverings $con
> trols_main_model [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 61 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     88,579
Absorbing 2 HDFE groups                           F(  53,   2335) =      25.69
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3269
                                                  Adj R-squared   =     0.3061
                                                  Within R-sq.    =     0.0810
Number of clusters (ctyfip)  =      2,336         Root MSE        =     0.3227

                                     (Std. err. adjusted for 2,336 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |    .191723   .0164469    11.66   0.000     .1594709    .2239751
         indep_third |   .0923414   .0196303     4.70   0.000     .0538468     .130836
          dmonthdum4 |   .0108319   .0211444     0.51   0.609     -.030632    .0522957
          dmonthdum5 |    .041352   .0217965     1.90   0.058    -.0013904    .0840945
          dmonthdum6 |  -.0471414   .0201857    -2.34   0.020    -.0867252   -.0075577
          dmonthdum7 |  -.0924718   .0210013    -4.40   0.000    -.1336549   -.0512886
          dmonthdum8 |  -.1052346   .0297855    -3.53   0.000    -.1636433   -.0468259
          dmonthdum9 |  -.0390256   .0355588    -1.10   0.273    -.1087558    .0307045
         dmonthdum10 |  -.0421384   .0321365    -1.31   0.190    -.1051575    .0208807
         dmonthdum11 |  -.0614523   .0250105    -2.46   0.014    -.1104975   -.0124072
         dmonthdum12 |  -.0874137   .0225444    -3.88   0.000    -.1316227   -.0432046
         dmonthdum13 |  -.0263828   .0251163    -1.05   0.294    -.0756354    .0228698
         dmonthdum14 |  -.0521778   .0220933    -2.36   0.018    -.0955024   -.0088532
         dmonthdum15 |    .003033   .0276264     0.11   0.913    -.0511419     .057208
         dmonthdum16 |   .1069854   .0260748     4.10   0.000     .0558532    .1581175
         dmonthdum17 |   .1797746   .0259208     6.94   0.000     .1289445    .2306047
         dmonthdum18 |   .2092315   .0337687     6.20   0.000     .1430117    .2754513
         dmonthdum19 |   .2478435    .030509     8.12   0.000     .1880158    .3076711
         dmonthdum20 |   .2201983   .0260398     8.46   0.000     .1691348    .2712618
          imonthdum4 |   .0096047    .027435     0.35   0.726    -.0441947    .0634042
          imonthdum5 |   .0308795    .026371     1.17   0.242    -.0208335    .0825926
          imonthdum6 |  -.0034102   .0245195    -0.14   0.889    -.0514925     .044672
          imonthdum7 |   .0045371   .0256239     0.18   0.859    -.0457109    .0547851
          imonthdum8 |  -.0689057   .0436071    -1.58   0.114    -.1544184    .0166069
          imonthdum9 |  -.0603407   .0551001    -1.10   0.274    -.1683909    .0477095
         imonthdum10 |  -.0009322   .0427124    -0.02   0.983    -.0846904     .082826
         imonthdum11 |   .0294072   .0311788     0.94   0.346    -.0317337    .0905482
         imonthdum12 |  -.0093138     .02868    -0.32   0.745    -.0655547    .0469271
         imonthdum13 |   .0355274   .0317901     1.12   0.264    -.0268124    .0978672
         imonthdum14 |   .0101446   .0291446     0.35   0.728    -.0470073    .0672966
         imonthdum15 |   .0361761   .0329115     1.10   0.272    -.0283628     .100715
         imonthdum16 |    .063923   .0363122     1.76   0.078    -.0072846    .1351306
         imonthdum17 |   .1521175   .0349557     4.35   0.000       .08357     .220665
         imonthdum18 |   .0933916   .0419052     2.23   0.026     .0112162    .1755669
         imonthdum19 |   .1066747   .0396851     2.69   0.007      .028853    .1844963
         imonthdum20 |   .1526034   .0364338     4.19   0.000     .0811575    .2240493
ZLNpc_new_cases_7day |   .0342334   .0039917     8.58   0.000     .0264057    .0420611
       out_workforce |  -.0151083   .0117881    -1.28   0.200    -.0382245    .0080079
            employed |  -.0141912   .0106067    -1.34   0.181    -.0349907    .0066083
              income |   .0002488   .0014639     0.17   0.865    -.0026218    .0031195
Y3h6_facialcoverings |   .0133177   .0072129     1.85   0.065    -.0008266     .027462
                male |  -.0357641   .0055368    -6.46   0.000    -.0466215   -.0249066
               age10 |   .0119704   .0033346     3.59   0.000     .0054314    .0185094
          age_group4 |   .0227974   .0108082     2.11   0.035     .0016027    .0439921
     live_w_children |  -.0195026   .0066679    -2.92   0.003    -.0325782   -.0064269
             somecol |   .0244423   .0088246     2.77   0.006     .0071375    .0417472
                  ba |   .0469178   .0096723     4.85   0.000     .0279507     .065885
                grad |   .0591634   .0086652     6.83   0.000     .0421711    .0761557
             AmerInd |   .0092737    .054984     0.17   0.866    -.0985489    .1170964
               Asian |   .0250028   .0182674     1.37   0.171    -.0108192    .0608249
               Black |    .015251   .0090802     1.68   0.093     -.002555    .0330571
                Hisp |   .0042817   .0078545     0.55   0.586    -.0111208    .0196841
         Multiracial |  -.0078541   .0215908    -0.36   0.716    -.0501932     .034485
               _cons |   .6219537   .0212732    29.24   0.000     .5802374      .66367
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       269           1         268     |
      ctyfip |      2336        2336           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Mask", replace) ///
> title("Worn mask (base month April 2020)") xtitle("Pandemic Month")
(file Mask.gph not found)
file Mask.gph saved

. 
. *Very Worried Ill
. 
. estimates clear

. reghdfe v_worry_ill dmonthdum4-dmonthdum20 imonthdum4-imonthdum20  $controls_fe_model Yc4_restrictionsongatherings Yc6_stayat
> homerequirements [aw=WEIGHT]  if minmonthworry==4  , a(time pid) vce(cl ctyfip)
(dropped 1241 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     43,121
Absorbing 2 HDFE groups                           F(  40,   1886) =       4.09
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6532
                                                  Adj R-squared   =     0.4848
                                                  Within R-sq.    =     0.0148
Number of clusters (ctyfip)  =      1,887         Root MSE        =     0.2233

                                             (Std. err. adjusted for 1,887 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum4 |  -.0315896    .019915    -1.59   0.113    -.0706473    .0074682
                  dmonthdum5 |  -.0155635   .0165062    -0.94   0.346    -.0479358    .0168089
                  dmonthdum6 |   .0551676   .0206523     2.67   0.008     .0146639    .0956713
                  dmonthdum7 |   .0656367   .0195151     3.36   0.001     .0273632    .1039101
                  dmonthdum8 |    .071267   .0414522     1.72   0.086    -.0100301     .152564
                  dmonthdum9 |   .0803299   .0305845     2.63   0.009      .020347    .1403129
                 dmonthdum10 |   .1009538   .0429679     2.35   0.019     .0166842    .1852234
                 dmonthdum11 |   .0296738   .0287263     1.03   0.302    -.0266648    .0860124
                 dmonthdum12 |    .000116   .0238639     0.00   0.996    -.0466865    .0469185
                 dmonthdum13 |    .018046   .0291318     0.62   0.536     -.039088      .07518
                 dmonthdum14 |  -.0393146   .0223542    -1.76   0.079    -.0831563     .004527
                 dmonthdum15 |  -.0692261   .0255865    -2.71   0.007     -.119407   -.0190453
                 dmonthdum16 |  -.1296107   .0248595    -5.21   0.000    -.1783657   -.0808557
                 dmonthdum17 |  -.0913691   .0223067    -4.10   0.000    -.1351175   -.0476207
                 dmonthdum18 |  -.0848452   .0309413    -2.74   0.006    -.1455281   -.0241623
                 dmonthdum19 |  -.0589736   .0278971    -2.11   0.035     -.113686   -.0042612
                 dmonthdum20 |  -.0833566   .0251731    -3.31   0.001    -.1327267   -.0339866
                  imonthdum4 |   .0440916   .0212169     2.08   0.038     .0024806    .0857026
                  imonthdum5 |   .0406475   .0184935     2.20   0.028     .0043777    .0769173
                  imonthdum6 |   .0700644   .0238464     2.94   0.003     .0232963    .1168326
                  imonthdum7 |   .0359902   .0209376     1.72   0.086    -.0050732    .0770535
                  imonthdum8 |   .0315023   .0449684     0.70   0.484    -.0566907    .1196953
                  imonthdum9 |   .0869997   .0463847     1.88   0.061    -.0039711    .1779705
                 imonthdum10 |   .0402561   .0390408     1.03   0.303    -.0363116    .1168237
                 imonthdum11 |   .0010687   .0288273     0.04   0.970    -.0554681    .0576054
                 imonthdum12 |   .0311433   .0267796     1.16   0.245    -.0213775     .083664
                 imonthdum13 |   .0529788   .0270922     1.96   0.051    -.0001551    .1061126
                 imonthdum14 |   .0023272   .0255534     0.09   0.927    -.0477887    .0524431
                 imonthdum15 |   .0411825   .0284709     1.45   0.148    -.0146553    .0970204
                 imonthdum16 |   .0083062    .027621     0.30   0.764    -.0458647     .062477
                 imonthdum17 |   .0026596   .0246271     0.11   0.914    -.0456396    .0509588
                 imonthdum18 |   .0097792   .0241959     0.40   0.686    -.0376744    .0572329
                 imonthdum19 |  -.0009913   .0262493    -0.04   0.970     -.052472    .0504894
                 imonthdum20 |   .0019141   .0232818     0.08   0.934    -.0437467     .047575
        ZLNpc_new_cases_7day |   .0079375   .0042981     1.85   0.065    -.0004919     .016367
               out_workforce |  -.0753356   .0278366    -2.71   0.007    -.1299294   -.0207419
                    employed |  -.0551838   .0273845    -2.02   0.044    -.1088908   -.0014768
                      income |  -.0032066   .0039275    -0.82   0.414    -.0109093     .004496
Yc4_restrictionsongatherings |   -.002801   .0107186    -0.26   0.794    -.0238226    .0182207
  Yc6_stayathomerequirements |   .0083911   .0085151     0.99   0.325     -.008309    .0250911
                       _cons |   .1782111    .034841     5.11   0.000     .1098801    .2465422
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       253           1         252     |
         pid |     13808       13808           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe v_worry_ill dem indep_third dmonthdum4-dmonthdum20 imonthdum4-imonthdum20 $controls_fe_model Yc4_restrictionsongather
> ings Yc6_stayathomerequirements $controls_main_model  [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 77 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =     85,502
Absorbing 2 HDFE groups                           F(  54,   2318) =      14.33
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1601
                                                  Adj R-squared   =     0.1333
                                                  Within R-sq.    =     0.0404
Number of clusters (ctyfip)  =      2,319         Root MSE        =     0.2881

                                             (Std. err. adjusted for 2,319 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .1151344   .0148449     7.76   0.000     .0860237    .1442451
                 indep_third |   .0418175   .0143468     2.91   0.004     .0136836    .0699514
                  dmonthdum4 |   .0099173    .015875     0.62   0.532    -.0212133    .0410479
                  dmonthdum5 |  -.0129588   .0164224    -0.79   0.430    -.0451628    .0192453
                  dmonthdum6 |    .069287   .0172052     4.03   0.000     .0355477    .1030262
                  dmonthdum7 |   .0624801   .0202765     3.08   0.002     .0227182     .102242
                  dmonthdum8 |   .0332857   .0294775     1.13   0.259    -.0245193    .0910907
                  dmonthdum9 |   .0198265    .029607     0.67   0.503    -.0382324    .0778854
                 dmonthdum10 |   .0963214   .0323867     2.97   0.003     .0328115    .1598313
                 dmonthdum11 |   .0402116   .0235603     1.71   0.088    -.0059899     .086413
                 dmonthdum12 |   .0404222    .019328     2.09   0.037     .0025202    .0783241
                 dmonthdum13 |   .0375585   .0219908     1.71   0.088    -.0055651    .0806822
                 dmonthdum14 |  -.0165605   .0185709    -0.89   0.373    -.0529777    .0198567
                 dmonthdum15 |   -.063323   .0170505    -3.71   0.000    -.0967589   -.0298872
                 dmonthdum16 |  -.0895314   .0180526    -4.96   0.000    -.1249324   -.0541304
                 dmonthdum17 |  -.0918655    .015276    -6.01   0.000    -.1218215   -.0619094
                 dmonthdum18 |  -.0857021   .0189849    -4.51   0.000    -.1229313   -.0484729
                 dmonthdum19 |  -.0500285   .0196845    -2.54   0.011    -.0886296   -.0114274
                 dmonthdum20 |  -.0523834   .0181239    -2.89   0.004    -.0879242   -.0168426
                  imonthdum4 |   .0232321   .0171893     1.35   0.177    -.0104759    .0569401
                  imonthdum5 |   .0268653   .0165939     1.62   0.106    -.0056751    .0594057
                  imonthdum6 |   .0598874   .0199923     3.00   0.003     .0206828    .0990921
                  imonthdum7 |   .0725184   .0205439     3.53   0.000      .032232    .1128047
                  imonthdum8 |  -.0016584   .0326727    -0.05   0.960    -.0657292    .0624124
                  imonthdum9 |   .0637674   .0370096     1.72   0.085    -.0088081    .1363428
                 imonthdum10 |   .0701936   .0358606     1.96   0.050    -.0001285    .1405157
                 imonthdum11 |   .0159017    .026425     0.60   0.547    -.0359173    .0677207
                 imonthdum12 |   .0271866   .0209778     1.30   0.195    -.0139507    .0683239
                 imonthdum13 |   .0449183   .0233816     1.92   0.055    -.0009326    .0907693
                 imonthdum14 |   .0063374   .0176476     0.36   0.720    -.0282692    .0409441
                 imonthdum15 |   .0123024   .0175275     0.70   0.483    -.0220689    .0466737
                 imonthdum16 |  -.0330103   .0173329    -1.90   0.057    -.0669999    .0009793
                 imonthdum17 |  -.0176493    .015947    -1.11   0.269    -.0489212    .0136226
                 imonthdum18 |  -.0107177   .0174387    -0.61   0.539    -.0449147    .0234793
                 imonthdum19 |   -.022927   .0197175    -1.16   0.245    -.0615928    .0157388
                 imonthdum20 |   .0219527   .0201093     1.09   0.275    -.0174813    .0613868
        ZLNpc_new_cases_7day |   .0097806   .0031968     3.06   0.002     .0035117    .0160494
               out_workforce |  -.0467642   .0158715    -2.95   0.003     -.077888   -.0156403
                    employed |  -.0444551   .0149538    -2.97   0.003    -.0737792   -.0151309
                      income |  -.0034169   .0013869    -2.46   0.014    -.0061367   -.0006972
Yc4_restrictionsongatherings |  -.0030966   .0076711    -0.40   0.686    -.0181396    .0119464
  Yc6_stayathomerequirements |   -.005884   .0065623    -0.90   0.370    -.0187526    .0069846
                        male |  -.0448114   .0060948    -7.35   0.000    -.0567634   -.0328595
                       age10 |   .0011296   .0027056     0.42   0.676    -.0041761    .0064352
                  age_group4 |  -.0327381   .0100638    -3.25   0.001    -.0524731    -.013003
             live_w_children |  -.0021033   .0069287    -0.30   0.761    -.0156904    .0114837
                     somecol |   .0090194   .0078039     1.16   0.248    -.0062841    .0243228
                          ba |  -.0025431   .0092872    -0.27   0.784    -.0207552     .015669
                        grad |   .0051337   .0093571     0.55   0.583    -.0132155     .023483
                     AmerInd |   .0197517   .0399134     0.49   0.621    -.0585179    .0980214
                       Asian |   .0218551   .0287384     0.76   0.447    -.0345005    .0782108
                       Black |  -.0203789   .0112014    -1.82   0.069    -.0423446    .0015869
                        Hisp |   .0198818   .0102391     1.94   0.052    -.0001969    .0399605
                 Multiracial |   .0191721   .0169282     1.13   0.258    -.0140238     .052368
                       _cons |   .1202943   .0224146     5.37   0.000     .0763395    .1642491
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       265           1         264     |
      ctyfip |      2319        2319           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Worry", replace) ///
> title("Very worried about COVID (base month April 2020)") xtitle("Pandemic Month")
(file Worry.gph not found)
file Worry.gph saved

. 
. 
. *Mostly Remote
. 
. estimates clear

. reghdfe mostly_remote dmonthdum5-dmonthdum20 imonthdum5-imonthdum20  ZLNpc_new_cases_7day income Yc4_restrictionsongatherings
>  Yc6_stayathomerequirements Yc2_workplaceclosing  [aw=WEIGHT]  if (minmonthmostly_remote==4 | minmonthmostly_remote==5)  &  e
> mployed==1, a(time pid) vce(cl ctyfip)
(dropped 1177 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =     17,258
Absorbing 2 HDFE groups                           F(  37,   1289) =       1.15
Statistics robust to heteroskedasticity           Prob > F        =     0.2464
                                                  R-squared       =     0.8057
                                                  Adj R-squared   =     0.7015
                                                  Within R-sq.    =     0.0064
Number of clusters (ctyfip)  =      1,290         Root MSE        =     0.2732

                                             (Std. err. adjusted for 1,290 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum5 |  -.0027909   .0328974    -0.08   0.932    -.0673291    .0617474
                  dmonthdum6 |   .0141552   .0298272     0.47   0.635      -.04436    .0726704
                  dmonthdum7 |   .0588027   .0379699     1.55   0.122    -.0156868    .1332922
                  dmonthdum8 |  -.0494414   .0579941    -0.85   0.394    -.1632146    .0643317
                  dmonthdum9 |  -.0421938   .0779068    -0.54   0.588    -.1950319    .1106443
                 dmonthdum10 |   .0285995   .0766728     0.37   0.709    -.1218175    .1790166
                 dmonthdum11 |  -.0599273   .0468816    -1.28   0.201       -.1519    .0320454
                 dmonthdum12 |  -.0668316    .047632    -1.40   0.161    -.1602763    .0266131
                 dmonthdum13 |   -.049163   .0397017    -1.24   0.216      -.12705     .028724
                 dmonthdum14 |   .0410318    .050923     0.81   0.421    -.0588693    .1409329
                 dmonthdum15 |   -.114091   .0557379    -2.05   0.041     -.223438    -.004744
                 dmonthdum16 |  -.0611291   .0516233    -1.18   0.237     -.162404    .0401458
                 dmonthdum17 |   -.018392   .0519179    -0.35   0.723    -.1202448    .0834608
                 dmonthdum18 |  -.0290566   .0529042    -0.55   0.583    -.1328444    .0747312
                 dmonthdum19 |  -.0192995   .0622477    -0.31   0.757    -.1414174    .1028183
                 dmonthdum20 |  -.0714488   .0545707    -1.31   0.191     -.178506    .0356083
                  imonthdum5 |  -.0153563   .0445104    -0.35   0.730     -.102677    .0719644
                  imonthdum6 |   .0051784   .0342718     0.15   0.880    -.0620562     .072413
                  imonthdum7 |   -.010106   .0353125    -0.29   0.775    -.0793823    .0591704
                  imonthdum8 |  -.1060343    .074904    -1.42   0.157    -.2529815    .0409128
                  imonthdum9 |  -.0999622   .0733285    -1.36   0.173    -.2438185     .043894
                 imonthdum10 |   .0217614   .0770564     0.28   0.778    -.1294082    .1729311
                 imonthdum11 |  -.0628395   .0549954    -1.14   0.253    -.1707299    .0450508
                 imonthdum12 |  -.0576232   .0551647    -1.04   0.296    -.1658457    .0505994
                 imonthdum13 |  -.0321058   .0545829    -0.59   0.557    -.1391869    .0749754
                 imonthdum14 |   .0215908   .0515315     0.42   0.675    -.0795039    .1226856
                 imonthdum15 |  -.0764715   .0644907    -1.19   0.236    -.2029899    .0500468
                 imonthdum16 |   .0153308    .069019     0.22   0.824     -.120071    .1507327
                 imonthdum17 |   .0078514   .0555025     0.14   0.888    -.1010336    .1167365
                 imonthdum18 |    .031697   .0589339     0.54   0.591      -.08392    .1473139
                 imonthdum19 |   .0027937   .0691452     0.04   0.968    -.1328557    .1384431
                 imonthdum20 |  -.1411751    .058993    -2.39   0.017    -.2569079   -.0254423
        ZLNpc_new_cases_7day |  -.0064095   .0082533    -0.78   0.438    -.0226009    .0097819
                      income |  -.0064916   .0084049    -0.77   0.440    -.0229802    .0099971
Yc4_restrictionsongatherings |  -.0292104   .0198203    -1.47   0.141     -.068094    .0096731
  Yc6_stayathomerequirements |   -.006567   .0140543    -0.47   0.640    -.0341387    .0210047
        Yc2_workplaceclosing |   .0038823   .0135419     0.29   0.774    -.0226843    .0304489
                       _cons |   .5694024   .0557147    10.22   0.000     .4601009    .6787039
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       236           1         235     |
         pid |      5755        5755           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. reghdfe mostly_remote dem indep_third  dmonthdum5-dmonthdum20 imonthdum5-imonthdum20 ZLNpc_new_cases_7day  income Yc4_restric
> tionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing  $controls_main_model  if  employed==1 [aw=WEIGHT], a(time 
> ctyfip) vce(cl ctyfip)
(dropped 168 singleton observations)
(MWFE estimator converged in 9 iterations)

HDFE Linear regression                            Number of obs   =     38,422
Absorbing 2 HDFE groups                           F(  51,   1788) =      27.57
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3477
                                                  Adj R-squared   =     0.3102
                                                  Within R-sq.    =     0.1210
Number of clusters (ctyfip)  =      1,789         Root MSE        =     0.4135

                                             (Std. err. adjusted for 1,789 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .1462206   .0255274     5.73   0.000      .096154    .1962872
                 indep_third |   .0730918   .0288984     2.53   0.012     .0164136    .1297701
                  dmonthdum5 |   .0007647    .031706     0.02   0.981    -.0614199    .0629494
                  dmonthdum6 |   .0125133    .030213     0.41   0.679    -.0467432    .0717698
                  dmonthdum7 |    .009031   .0371445     0.24   0.808    -.0638201    .0818822
                  dmonthdum8 |   .0886296   .0592587     1.50   0.135     -.027594    .2048531
                  dmonthdum9 |  -.0353979   .0655957    -0.54   0.590    -.1640502    .0932545
                 dmonthdum10 |   .0408243   .0566621     0.72   0.471    -.0703066    .1519552
                 dmonthdum11 |    .052176   .0409547     1.27   0.203    -.0281482    .1325001
                 dmonthdum12 |  -.0121666   .0378011    -0.32   0.748    -.0863056    .0619724
                 dmonthdum13 |  -.0292824   .0378476    -0.77   0.439    -.1035126    .0449478
                 dmonthdum14 |   .0042762   .0426181     0.10   0.920    -.0793104    .0878628
                 dmonthdum15 |  -.0831728   .0412737    -2.02   0.044    -.1641226    -.002223
                 dmonthdum16 |  -.0654646   .0403076    -1.62   0.105    -.1445195    .0135903
                 dmonthdum17 |  -.0478673   .0383525    -1.25   0.212    -.1230877    .0273532
                 dmonthdum18 |   -.049562   .0402948    -1.23   0.219    -.1285918    .0294678
                 dmonthdum19 |  -.0212842   .0394726    -0.54   0.590    -.0987015     .056133
                 dmonthdum20 |  -.1227259   .0407838    -3.01   0.003    -.2027147    -.042737
                  imonthdum5 |   .0117199   .0405188     0.29   0.772    -.0677493    .0911891
                  imonthdum6 |  -.0105241   .0367833    -0.29   0.775    -.0826669    .0616187
                  imonthdum7 |   .0302482   .0402133     0.75   0.452    -.0486218    .1091183
                  imonthdum8 |   .0704828   .0706855     1.00   0.319    -.0681521    .2091178
                  imonthdum9 |  -.0750944   .0652265    -1.15   0.250    -.2030226    .0528339
                 imonthdum10 |   .0062528   .0576488     0.11   0.914    -.1068134     .119319
                 imonthdum11 |    .027625   .0438835     0.63   0.529    -.0584434    .1136933
                 imonthdum12 |  -.0450961   .0407955    -1.11   0.269     -.125108    .0349158
                 imonthdum13 |  -.0153701   .0426742    -0.36   0.719    -.0990667    .0683265
                 imonthdum14 |   .0437509    .044934     0.97   0.330    -.0443779    .1318796
                 imonthdum15 |   .0031449    .048343     0.07   0.948    -.0916697    .0979595
                 imonthdum16 |  -.0376269   .0505359    -0.74   0.457    -.1367426    .0614888
                 imonthdum17 |   .0116559   .0414804     0.28   0.779    -.0696992     .093011
                 imonthdum18 |   .0446404    .049703     0.90   0.369    -.0528417    .1421225
                 imonthdum19 |   .0354697   .0427957     0.83   0.407     -.048465    .1194045
                 imonthdum20 |  -.0643309   .0433235    -1.48   0.138    -.1493009    .0206391
        ZLNpc_new_cases_7day |  -.0019305   .0063479    -0.30   0.761    -.0143806    .0105195
                      income |   .0349439   .0030786    11.35   0.000     .0289058    .0409821
Yc4_restrictionsongatherings |  -.0102804   .0139748    -0.74   0.462    -.0376892    .0171283
  Yc6_stayathomerequirements |   .0118389   .0139242     0.85   0.395    -.0154705    .0391482
        Yc2_workplaceclosing |  -.0074264     .01061    -0.70   0.484    -.0282358     .013383
                        male |  -.0905511   .0130468    -6.94   0.000    -.1161397   -.0649625
                       age10 |  -.0150427   .0058562    -2.57   0.010    -.0265285    -.003557
                  age_group4 |   .0155658   .0237524     0.66   0.512    -.0310196    .0621513
             live_w_children |  -.0382197   .0126361    -3.02   0.003    -.0630027   -.0134367
                     somecol |   .0576769   .0178218     3.24   0.001     .0227232    .0926307
                          ba |   .2482401   .0213951    11.60   0.000     .2062782    .2902021
                        grad |   .2411652   .0207682    11.61   0.000     .2004327    .2818977
                     AmerInd |  -.1276186    .088204    -1.45   0.148    -.3006123    .0453752
                       Asian |   .0471461   .0449039     1.05   0.294    -.0409235    .1352157
                       Black |   .0094218    .022591     0.42   0.677    -.0348857    .0537293
                        Hisp |  -.0142118   .0236002    -0.60   0.547    -.0604987    .0320751
                 Multiracial |  -.1073537   .0305351    -3.52   0.000    -.1672419   -.0474654
                       _cons |   .1618385   .0377501     4.29   0.000     .0877995    .2358775
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       247           1         246     |
      ctyfip |      1789        1789           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Remote", replace) ///
> title("Mostly working remote (base month May 2020)") xtitle("Pandemic Month")
(file Remote.gph not found)
file Remote.gph saved

. 
. grc1leg MostlyIsolate.gph Mask.gph Worry.gph Remote.gph   ///
> , imargin(2 2 2 2) row(2) col(2) legendfrom(MostlyIsolate.gph) iscale(*.75) plotregion(color(white)) graphregion(color(white)
> )  

. graph export "figures\Figure S10.png", replace width(2200) height(1600)
file figures\Figure S10.png saved as PNG format

. 
. * Delete the intermediate files
. erase MostlyIsolate.gph

. erase Mask.gph

. erase Worry.gph

. erase Remote.gph

. 
. 
. ******************
. *** Figure S11 ***
. ******************
. 
. *Change in Partisan Gap in COVID-19 Responses, Initial Party Identification
. 
. clear

. use "data_gallup.dta"

. 
. bysort pid: gen firstinpanel=1 if _n==1
(110,111 missing values generated)

. bysort pid: replace firstinpanel=0 if _n!=1
(110111 real changes made)

. 
. gen firstdem=1 if firstinpanel==1 & dem==1
(143,006 missing values generated)

. replace firstdem=0 if firstinpanel==1 & dem==0
(29,942 real changes made)

. bysort pid (firstdem): replace firstdem= firstdem[1]
(104064 real changes made)

. 
. gen firstind=1 if firstinpanel==1 & indep_third==1
(150,882 missing values generated)

. replace firstind=0 if firstinpanel==1 & indep_third==0
(37,818 real changes made)

. bysort pid (firstind): replace firstind= firstind[1]
(104064 real changes made)

. 
. gen firstgop=1 if firstinpanel==1 & gop==1
(147,830 missing values generated)

. replace firstgop=0 if firstinpanel==1 & gop==0
(34,766 real changes made)

. bysort pid (firstgop): replace firstgop= firstgop[1]
(104064 real changes made)

. 
. replace dem=firstdem
(17,041 real changes made, 5,804 to missing)

. replace indep_third=firstind
(22,238 real changes made, 5,804 to missing)

. drop dmonth imonth

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(4,143 real changes made)
(3,759 real changes made)
(3,905 real changes made)
(3,731 real changes made)
(3,572 real changes made)
(4,843 real changes made)
(3,475 real changes made)
(3,553 real changes made)
(4,034 real changes made)

. egen minmonthvac=min(month_number) if vaccinated!=., by(pid)
(264 missing values generated)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(30,507 missing values generated)

. egen minmonthisol=min(month_number) if Mostly_Isol!=., by(pid)
(5,890 missing values generated)

. egen minmonthworry=min(month_number) if v_worry_ill!=., by(pid)
(35,223 missing values generated)

. egen minmonthmostly_remote=min(month_number) if mostly_remote!=., by(pid)
(108,466 missing values generated)

. 
. gen dmonth=dem*month_number
(9,000 missing values generated)

. gen imonth=indep_third*month_number
(9,000 missing values generated)

. 
. drop dmonthdum* imonthdum*

. 
. *recreate month X party dummies with initial party ID
. tab dmonth, gen(dmonthdum)

     dmonth |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |     90,947       58.55       58.55
          3 |      8,330        5.36       63.91
          4 |     13,311        8.57       72.48
          5 |      7,061        4.55       77.03
          6 |      6,235        4.01       81.04
          7 |      6,511        4.19       85.24
          8 |      4,474        2.88       88.12
          9 |      1,072        0.69       88.81
         10 |      1,203        0.77       89.58
         11 |      1,225        0.79       90.37
         12 |      1,244        0.80       91.17
         13 |      1,675        1.08       92.25
         14 |      1,371        0.88       93.13
         15 |      1,570        1.01       94.14
         16 |      1,454        0.94       95.08
         17 |      1,425        0.92       96.00
         18 |      1,911        1.23       97.23
         19 |      1,407        0.91       98.13
         20 |      1,373        0.88       99.02
         21 |      1,528        0.98      100.00
------------+-----------------------------------
      Total |    155,327      100.00

. tab imonth, gen(imonthdum)

     imonth |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    113,849       73.30       73.30
          3 |      5,277        3.40       76.69
          4 |      8,207        5.28       81.98
          5 |      4,457        2.87       84.85
          6 |      3,955        2.55       87.39
          7 |      4,156        2.68       90.07
          8 |      2,884        1.86       91.93
          9 |        708        0.46       92.38
         10 |        738        0.48       92.86
         11 |        740        0.48       93.33
         12 |        792        0.51       93.84
         13 |      1,116        0.72       94.56
         14 |      1,012        0.65       95.21
         15 |      1,033        0.67       95.88
         16 |      1,085        0.70       96.58
         17 |        977        0.63       97.21
         18 |      1,292        0.83       98.04
         19 |        918        0.59       98.63
         20 |        959        0.62       99.25
         21 |      1,172        0.75      100.00
------------+-----------------------------------
      Total |    155,327      100.00

. 
. *Mostly Isolate
. estimates clear

. reghdfe Mostly_Isol  dem indep_third dmonthdum3-dmonthdum20 imonthdum3-imonthdum20  Yc4_restrictionsongatherings Yc6_stayatho
> merequirements $controls_fe_model [aw=WEIGHT]  if minmonthisol==3 ,  a(time pid) vce(cl ctyfip)
(dropped 1362 singleton observations)
(MWFE estimator converged in 12 iterations)
note: dem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: indep_third is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     55,308
Absorbing 2 HDFE groups                           F(  42,   1920) =       4.49
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5803
                                                  Adj R-squared   =     0.4293
                                                  Within R-sq.    =     0.0122
Number of clusters (ctyfip)  =      1,921         Root MSE        =     0.3775

                                             (Std. err. adjusted for 1,921 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |          0  (omitted)
                 indep_third |          0  (omitted)
                  dmonthdum3 |   .0947359   .0262864     3.60   0.000      .043183    .1462889
                  dmonthdum4 |   .1761986   .0324196     5.43   0.000     .1126172    .2397799
                  dmonthdum5 |    .148261    .032378     4.58   0.000     .0847614    .2117607
                  dmonthdum6 |   .1381648   .0344367     4.01   0.000     .0706276    .2057019
                  dmonthdum7 |   .2076489   .0410192     5.06   0.000     .1272021    .2880957
                  dmonthdum8 |   .2008878   .0762251     2.64   0.008     .0513952    .3503805
                  dmonthdum9 |   .1607615   .0694732     2.31   0.021     .0245107    .2970124
                 dmonthdum10 |   .1380735   .0828302     1.67   0.096     -.024373    .3005201
                 dmonthdum11 |   .1327014   .0429739     3.09   0.002     .0484209    .2169819
                 dmonthdum12 |   .1999849   .0375574     5.32   0.000     .1263272    .2736425
                 dmonthdum13 |   .1319376    .043172     3.06   0.002     .0472686    .2166065
                 dmonthdum14 |   .2140748   .0444938     4.81   0.000     .1268136     .301336
                 dmonthdum15 |   .1069426   .0531787     2.01   0.044     .0026484    .2112367
                 dmonthdum16 |   .1047373   .0464778     2.25   0.024     .0135851    .1958895
                 dmonthdum17 |   .0224002   .0425245     0.53   0.598    -.0609988    .1057993
                 dmonthdum18 |  -.0267471     .04859    -0.55   0.582    -.1220419    .0685477
                 dmonthdum19 |   .1367474   .0472735     2.89   0.004     .0440346    .2294602
                 dmonthdum20 |   .0110164   .0470843     0.23   0.815    -.0813253    .1033581
                  imonthdum3 |   .0750581    .030176     2.49   0.013     .0158769    .1342393
                  imonthdum4 |   .1353002   .0339004     3.99   0.000     .0688147    .2017858
                  imonthdum5 |   .0950249   .0351406     2.70   0.007     .0261072    .1639426
                  imonthdum6 |   .0853254   .0355232     2.40   0.016     .0156573    .1549935
                  imonthdum7 |   .1882557   .0405548     4.64   0.000     .1087196    .2677917
                  imonthdum8 |   .1933934   .0817086     2.37   0.018     .0331464    .3536404
                  imonthdum9 |   .1881583   .0727137     2.59   0.010     .0455523    .3307644
                 imonthdum10 |   .0580598   .0911197     0.64   0.524    -.1206442    .2367637
                 imonthdum11 |   .1448983   .0522002     2.78   0.006     .0425234    .2472733
                 imonthdum12 |    .102326    .039392     2.60   0.009     .0250704    .1795816
                 imonthdum13 |   .1411614    .044794     3.15   0.002     .0533115    .2290113
                 imonthdum14 |   .2105184   .0526756     4.00   0.000     .1072111    .3138258
                 imonthdum15 |   .0925303   .0586575     1.58   0.115    -.0225089    .2075695
                 imonthdum16 |   .0918888   .0463314     1.98   0.047     .0010236    .1827541
                 imonthdum17 |   .0913834   .0409264     2.23   0.026     .0111185    .1716484
                 imonthdum18 |   .0351415   .0523466     0.67   0.502    -.0675206    .1378036
                 imonthdum19 |   .1645721   .0497193     3.31   0.001     .0670626    .2620817
                 imonthdum20 |   .0333387   .0459706     0.73   0.468    -.0568188    .1234962
Yc4_restrictionsongatherings |  -.0000256   .0145511    -0.00   0.999    -.0285632     .028512
  Yc6_stayathomerequirements |   .0091768   .0114553     0.80   0.423    -.0132894     .031643
        ZLNpc_new_cases_7day |   .0194188   .0057236     3.39   0.001     .0081936     .030644
               out_workforce |  -.0209135   .0368474    -0.57   0.570    -.0931785    .0513516
                    employed |  -.1111179   .0300753    -3.69   0.000    -.1701015   -.0521342
                      income |  -.0003964   .0060759    -0.07   0.948    -.0123125    .0115197
                       _cons |   .5289885   .0499182    10.60   0.000     .4310889    .6268881
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       276           1         275     |
         pid |     14323       14323           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe Mostly_Isol dem indep_third dmonthdum3-dmonthdum20 imonthdum3-imonthdum20 Yc4_restrictionsongatherings Yc6_stayathome
> requirements $controls_main_model $controls_fe_model  [aw=WEIGHT],  a(time ctyfip) vce(cl ctyfip)
(dropped 106 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =    135,118
Absorbing 2 HDFE groups                           F(  56,   2509) =      48.90
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2553
                                                  Adj R-squared   =     0.2392
                                                  Within R-sq.    =     0.0713
Number of clusters (ctyfip)  =      2,510         Root MSE        =     0.4361

                                             (Std. err. adjusted for 2,510 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .0679531   .0190795     3.56   0.000     .0305399    .1053664
                 indep_third |   .0407552   .0208722     1.95   0.051    -.0001733    .0816838
                  dmonthdum3 |   .0642869   .0197731     3.25   0.001     .0255136    .1030601
                  dmonthdum4 |   .1724709   .0249821     6.90   0.000     .1234833    .2214585
                  dmonthdum5 |   .1786767   .0248425     7.19   0.000     .1299628    .2273907
                  dmonthdum6 |   .1873901   .0256499     7.31   0.000     .1370929    .2376874
                  dmonthdum7 |   .1929781   .0291433     6.62   0.000     .1358308    .2501255
                  dmonthdum8 |   .2060621    .044856     4.59   0.000     .1181035    .2940207
                  dmonthdum9 |   .1741891   .0452631     3.85   0.000     .0854323    .2629459
                 dmonthdum10 |   .1891329   .0485155     3.90   0.000     .0939984    .2842673
                 dmonthdum11 |   .1982667   .0311065     6.37   0.000     .1372698    .2592637
                 dmonthdum12 |   .1814944   .0269192     6.74   0.000     .1287082    .2342806
                 dmonthdum13 |   .1896863   .0290949     6.52   0.000     .1326337    .2467388
                 dmonthdum14 |   .1937187   .0283977     6.82   0.000     .1380333    .2494041
                 dmonthdum15 |   .0908362   .0285698     3.18   0.001     .0348133    .1468591
                 dmonthdum16 |   .0705125   .0269496     2.62   0.009     .0176668    .1233583
                 dmonthdum17 |   .0236713   .0261536     0.91   0.366    -.0276135    .0749562
                 dmonthdum18 |  -.0113639   .0277758    -0.41   0.682    -.0658297     .043102
                 dmonthdum19 |   .0495253   .0283215     1.75   0.080    -.0060107    .1050613
                 dmonthdum20 |   .0321071   .0276955     1.16   0.246    -.0222013    .0864156
                  imonthdum3 |    .025997   .0214993     1.21   0.227    -.0161612    .0681551
                  imonthdum4 |   .0885243   .0269752     3.28   0.001     .0356284    .1414201
                  imonthdum5 |   .1020808   .0260526     3.92   0.000     .0509941    .1531675
                  imonthdum6 |   .0987005   .0258394     3.82   0.000     .0480317    .1493693
                  imonthdum7 |   .1397896    .030354     4.61   0.000      .080268    .1993111
                  imonthdum8 |   .1383143   .0488074     2.83   0.005     .0426075    .2340211
                  imonthdum9 |   .1476767   .0491627     3.00   0.003     .0512732    .2440803
                 imonthdum10 |   .0371216   .0545156     0.68   0.496    -.0697786    .1440217
                 imonthdum11 |   .1605551   .0343476     4.67   0.000     .0932026    .2279077
                 imonthdum12 |   .0720176   .0299664     2.40   0.016     .0132562    .1307789
                 imonthdum13 |   .1244029   .0340426     3.65   0.000     .0576484    .1911573
                 imonthdum14 |   .1331543   .0296086     4.50   0.000     .0750946     .191214
                 imonthdum15 |   .1110368   .0304867     3.64   0.000      .051255    .1708185
                 imonthdum16 |   .0703822   .0278947     2.52   0.012     .0156832    .1250812
                 imonthdum17 |   .0533708   .0269524     1.98   0.048     .0005196     .106222
                 imonthdum18 |    .054716   .0286067     1.91   0.056    -.0013792    .1108113
                 imonthdum19 |   .0548839    .031295     1.75   0.080    -.0064828    .1162507
                 imonthdum20 |   .0326601    .027085     1.21   0.228    -.0204511    .0857713
Yc4_restrictionsongatherings |   -.003079   .0094477    -0.33   0.745    -.0216051    .0154471
  Yc6_stayathomerequirements |   .0078447   .0077692     1.01   0.313    -.0073899    .0230794
                        male |    -.04508   .0064471    -6.99   0.000    -.0577222   -.0324379
                       age10 |  -.0176471   .0031371    -5.63   0.000    -.0237988   -.0114955
                  age_group4 |   .0109722   .0112191     0.98   0.328    -.0110275     .032972
             live_w_children |  -.0360217   .0076855    -4.69   0.000    -.0510922   -.0209512
                     somecol |   .0231699   .0088855     2.61   0.009     .0057464    .0405935
                          ba |   .0860318   .0114357     7.52   0.000     .0636074    .1084561
                        grad |   .1144846   .0102047    11.22   0.000     .0944741     .134495
                     AmerInd |  -.0192519   .0462782    -0.42   0.677    -.1099992    .0714954
                       Asian |   .0084741   .0299618     0.28   0.777    -.0502782    .0672264
                       Black |  -.0318682   .0119225    -2.67   0.008    -.0552473   -.0084892
                        Hisp |   .0024102   .0110072     0.22   0.827    -.0191739    .0239943
                 Multiracial |  -.0130527   .0184156    -0.71   0.479    -.0491642    .0230587
        ZLNpc_new_cases_7day |   .0225558   .0035023     6.44   0.000     .0156881    .0294235
               out_workforce |    .012815   .0152316     0.84   0.400    -.0170528    .0426828
                    employed |  -.1707708   .0132944   -12.85   0.000      -.19684   -.1447015
                      income |   .0047841   .0016624     2.88   0.004     .0015242     .008044
                       _cons |   .5384164   .0237659    22.65   0.000     .4918136    .5850191
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       289           1         288     |
      ctyfip |      2510        2510           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("MostlyIsolate", replace) ///
> title("Mostly Isolating (base month March 2020)") xtitle("Pandemic Month")
(file MostlyIsolate.gph not found)
file MostlyIsolate.gph saved

. 
. *Worn Masks
. 
. estimates clear

. reghdfe worn_mask dem indep_third dmonthdum4-dmonthdum20 imonthdum4-imonthdum20  $controls_fe_model  Y3h6_facialcoverings [aw
> =WEIGHT]  if minmonthmask==4  , a(time pid) vce(cl ctyfip)
(dropped 3548 singleton observations)
(MWFE estimator converged in 12 iterations)
note: dem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: indep_third is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     62,411
Absorbing 2 HDFE groups                           F(  39,   2115) =       8.34
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6210
                                                  Adj R-squared   =     0.4454
                                                  Within R-sq.    =     0.0200
Number of clusters (ctyfip)  =      2,116         Root MSE        =     0.3046

                                     (Std. err. adjusted for 2,116 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |          0  (omitted)
         indep_third |          0  (omitted)
          dmonthdum4 |   .0646637   .0290191     2.23   0.026     .0077547    .1215727
          dmonthdum5 |   .0763322   .0251148     3.04   0.002       .02708    .1255844
          dmonthdum6 |  -.0060222   .0228826    -0.26   0.792     -.050897    .0388526
          dmonthdum7 |  -.0423489   .0244312    -1.73   0.083    -.0902607    .0055628
          dmonthdum8 |  -.0399797   .0448303    -0.89   0.373    -.1278958    .0479365
          dmonthdum9 |  -.0075075   .0421316    -0.18   0.859    -.0901313    .0751162
         dmonthdum10 |  -.0160624     .03469    -0.46   0.643    -.0840924    .0519676
         dmonthdum11 |   .0052048   .0314511     0.17   0.869    -.0564736    .0668831
         dmonthdum12 |  -.0656751   .0279942    -2.35   0.019     -.120574   -.0107761
         dmonthdum13 |  -.0179114   .0315332    -0.57   0.570    -.0797507    .0439279
         dmonthdum14 |  -.0163373    .030424    -0.54   0.591    -.0760014    .0433267
         dmonthdum15 |   .0241758   .0346236     0.70   0.485    -.0437241    .0920757
         dmonthdum16 |   .1402581   .0370449     3.79   0.000     .0676098    .2129063
         dmonthdum17 |   .2335666   .0351143     6.65   0.000     .1647044    .3024288
         dmonthdum18 |    .194275   .0459667     4.23   0.000     .1041304    .2844196
         dmonthdum19 |   .2735111   .0409436     6.68   0.000     .1932173    .3538049
         dmonthdum20 |   .2390424   .0317663     7.53   0.000      .176746    .3013388
          imonthdum4 |   .0791319   .0324454     2.44   0.015     .0155037    .1427601
          imonthdum5 |   .0296186   .0272685     1.09   0.278    -.0238573    .0830945
          imonthdum6 |    .026608    .026717     1.00   0.319    -.0257864    .0790024
          imonthdum7 |  -.0066943   .0276709    -0.24   0.809    -.0609594    .0475707
          imonthdum8 |   -.018419   .0478843    -0.38   0.701    -.1123242    .0754862
          imonthdum9 |  -.0440897   .0534483    -0.82   0.410    -.1489065    .0607271
         imonthdum10 |   .0410705    .042304     0.97   0.332    -.0418913    .1240323
         imonthdum11 |   .0446889   .0377072     1.19   0.236    -.0292582     .118636
         imonthdum12 |  -.0396701   .0314395    -1.26   0.207    -.1013256    .0219854
         imonthdum13 |  -.0014095   .0365651    -0.04   0.969    -.0731168    .0702978
         imonthdum14 |   .0147585   .0331014     0.45   0.656    -.0501561    .0796732
         imonthdum15 |   .0440876   .0380748     1.16   0.247    -.0305804    .1187555
         imonthdum16 |    .065312    .041105     1.59   0.112    -.0152984    .1459224
         imonthdum17 |   .1091032   .0433712     2.52   0.012     .0240487    .1941578
         imonthdum18 |   .0587572   .0515694     1.14   0.255    -.0423748    .1598892
         imonthdum19 |   .1216551   .0499594     2.44   0.015     .0236805    .2196297
         imonthdum20 |   .1034226   .0413825     2.50   0.013     .0222678    .1845773
ZLNpc_new_cases_7day |   .0357714   .0053411     6.70   0.000     .0252971    .0462457
       out_workforce |   .0010815   .0292801     0.04   0.971    -.0563392    .0585023
            employed |   .0168026   .0251175     0.67   0.504    -.0324549    .0660602
              income |  -.0034197   .0046605    -0.73   0.463    -.0125594    .0057199
Y3h6_facialcoverings |   .0193478    .009514     2.03   0.042     .0006901    .0380056
               _cons |   .7621292   .0362119    21.05   0.000     .6911145    .8331439
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       268           1         267     |
         pid |     19458       19458           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe worn_mask dem indep_third dmonthdum4-dmonthdum20 imonthdum4-imonthdum20 $controls_fe_model  Y3h6_facialcoverings $con
> trols_main_model [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 126 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =    113,641
Absorbing 2 HDFE groups                           F(  53,   2473) =      35.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3065
                                                  Adj R-squared   =     0.2890
                                                  Within R-sq.    =     0.0807
Number of clusters (ctyfip)  =      2,474         Root MSE        =     0.3344

                                     (Std. err. adjusted for 2,474 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |   .1654888   .0149669    11.06   0.000     .1361398    .1948378
         indep_third |   .0844645   .0165221     5.11   0.000      .052066    .1168631
          dmonthdum4 |   .0451114   .0190029     2.37   0.018     .0078482    .0823746
          dmonthdum5 |   .0684535   .0197369     3.47   0.001     .0297509     .107156
          dmonthdum6 |  -.0238216   .0194481    -1.22   0.221    -.0619579    .0143147
          dmonthdum7 |  -.0714687   .0194547    -3.67   0.000    -.1096179   -.0333194
          dmonthdum8 |  -.0806269   .0310402    -2.60   0.009    -.1414942   -.0197595
          dmonthdum9 |  -.0073802   .0307796    -0.24   0.811    -.0677367    .0529762
         dmonthdum10 |  -.0133829   .0298849    -0.45   0.654    -.0719849    .0452191
         dmonthdum11 |  -.0508211   .0225662    -2.25   0.024    -.0950718   -.0065705
         dmonthdum12 |  -.0621025   .0204373    -3.04   0.002    -.1021785   -.0220265
         dmonthdum13 |  -.0143965   .0227581    -0.63   0.527    -.0590233    .0302304
         dmonthdum14 |   -.030425    .020336    -1.50   0.135    -.0703023    .0094524
         dmonthdum15 |   .0314882   .0253064     1.24   0.214    -.0181358    .0811121
         dmonthdum16 |   .1339488   .0240843     5.56   0.000     .0867213    .1811763
         dmonthdum17 |   .2168715   .0232792     9.32   0.000     .1712228    .2625202
         dmonthdum18 |   .2317309   .0302128     7.67   0.000     .1724859    .2909759
         dmonthdum19 |   .2738745   .0277422     9.87   0.000     .2194741    .3282749
         dmonthdum20 |    .245185   .0247285     9.92   0.000     .1966944    .2936756
          imonthdum4 |   .0114618   .0259311     0.44   0.659    -.0393872    .0623108
          imonthdum5 |   .0206449   .0229785     0.90   0.369    -.0244142     .065704
          imonthdum6 |  -.0011314   .0227605    -0.05   0.960     -.045763    .0435003
          imonthdum7 |  -.0112098   .0227913    -0.49   0.623    -.0559018    .0334822
          imonthdum8 |  -.0642087   .0393742    -1.63   0.103    -.1414185    .0130011
          imonthdum9 |  -.0443139   .0421944    -1.05   0.294    -.1270538     .038426
         imonthdum10 |   .0151618   .0366524     0.41   0.679    -.0567107    .0870343
         imonthdum11 |  -.0126128   .0267698    -0.47   0.638    -.0651064    .0398807
         imonthdum12 |  -.0233665    .024077    -0.97   0.332    -.0705797    .0238466
         imonthdum13 |  -.0081728   .0277975    -0.29   0.769    -.0626816     .046336
         imonthdum14 |   .0098572   .0248311     0.40   0.691    -.0388347    .0585492
         imonthdum15 |   .0170241   .0285322     0.60   0.551    -.0389254    .0729736
         imonthdum16 |    .066862   .0309881     2.16   0.031     .0060966    .1276274
         imonthdum17 |   .1267855   .0292492     4.33   0.000       .06943    .1841409
         imonthdum18 |   .1023762   .0332963     3.07   0.002     .0370847    .1676676
         imonthdum19 |   .1000227    .034016     2.94   0.003       .03332    .1667255
         imonthdum20 |   .1421741   .0296355     4.80   0.000     .0840612     .200287
ZLNpc_new_cases_7day |   .0314845   .0037391     8.42   0.000     .0241525    .0388165
       out_workforce |   .0001923   .0120324     0.02   0.987    -.0234023    .0237869
            employed |  -.0082564   .0102224    -0.81   0.419    -.0283016    .0117889
              income |  -.0009895   .0013116    -0.75   0.451    -.0035614    .0015824
Y3h6_facialcoverings |   .0153054   .0067397     2.27   0.023     .0020892    .0285215
                male |  -.0471215   .0049132    -9.59   0.000     -.056756   -.0374871
               age10 |   .0115285   .0029261     3.94   0.000     .0057906    .0172664
          age_group4 |   .0162923   .0100358     1.62   0.105    -.0033871    .0359717
     live_w_children |  -.0202692   .0061397    -3.30   0.001    -.0323087   -.0082297
             somecol |   .0355942   .0075705     4.70   0.000      .020749    .0504394
                  ba |   .0684092   .0081548     8.39   0.000     .0524182    .0844002
                grad |   .0762601   .0074758    10.20   0.000     .0616006    .0909195
             AmerInd |   .0106207   .0422669     0.25   0.802    -.0722615    .0935029
               Asian |   .0351066   .0184352     1.90   0.057    -.0010435    .0712567
               Black |   .0149462   .0083881     1.78   0.075    -.0015021    .0313946
                Hisp |   .0034076   .0071747     0.47   0.635    -.0106614    .0174765
         Multiracial |  -.0230856   .0172097    -1.34   0.180    -.0568325    .0106612
               _cons |   .6206413   .0188323    32.96   0.000     .5837127    .6575699
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       269           1         268     |
      ctyfip |      2474        2474           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Mask", replace) ///
> title("Worn mask (base month April 2020)") xtitle("Pandemic Month")
(file Mask.gph not found)
file Mask.gph saved

. 
. *Very Worried Ill
. 
. estimates clear

. reghdfe v_worry_ill dem indep_third dmonthdum4-dmonthdum20 imonthdum4-imonthdum20  $controls_fe_model Yc4_restrictionsongathe
> rings Yc6_stayathomerequirements [aw=WEIGHT]  if minmonthworry==4  , a(time pid) vce(cl ctyfip)
(dropped 2929 singleton observations)
(MWFE estimator converged in 12 iterations)
note: dem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: indep_third is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     50,820
Absorbing 2 HDFE groups                           F(  40,   1994) =       4.69
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6415
                                                  Adj R-squared   =     0.4738
                                                  Within R-sq.    =     0.0134
Number of clusters (ctyfip)  =      1,995         Root MSE        =     0.2209

                                             (Std. err. adjusted for 1,995 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |          0  (omitted)
                 indep_third |          0  (omitted)
                  dmonthdum4 |  -.0284982   .0201837    -1.41   0.158    -.0680816    .0110851
                  dmonthdum5 |  -.0188831   .0160747    -1.17   0.240    -.0504081    .0126419
                  dmonthdum6 |   .0484552   .0183644     2.64   0.008     .0124398    .0844706
                  dmonthdum7 |   .0603594   .0177966     3.39   0.001     .0254575    .0952613
                  dmonthdum8 |   .0637464   .0387751     1.64   0.100    -.0122975    .1397904
                  dmonthdum9 |   .0930727   .0305671     3.04   0.002     .0331259    .1530195
                 dmonthdum10 |   .1109571   .0436974     2.54   0.011     .0252596    .1966545
                 dmonthdum11 |   .0197302   .0266174     0.74   0.459    -.0324706    .0719311
                 dmonthdum12 |   .0157782   .0229503     0.69   0.492    -.0292309    .0607873
                 dmonthdum13 |   .0103917   .0267103     0.39   0.697    -.0419913    .0627748
                 dmonthdum14 |  -.0459056   .0197763    -2.32   0.020      -.08469   -.0071211
                 dmonthdum15 |  -.0737035    .022976    -3.21   0.001     -.118763    -.028644
                 dmonthdum16 |  -.1201927   .0224646    -5.35   0.000    -.1642491   -.0761362
                 dmonthdum17 |  -.1092644   .0218467    -5.00   0.000    -.1521092   -.0664197
                 dmonthdum18 |   -.088023   .0280251    -3.14   0.002    -.1429845   -.0330614
                 dmonthdum19 |  -.0490569   .0286392    -1.71   0.087    -.1052227    .0071089
                 dmonthdum20 |  -.0840219   .0237522    -3.54   0.000    -.1306036   -.0374403
                  imonthdum4 |   .0407502   .0180385     2.26   0.024     .0053739    .0761265
                  imonthdum5 |   .0261018   .0168274     1.55   0.121    -.0068993    .0591029
                  imonthdum6 |   .0699392   .0206189     3.39   0.001     .0295023    .1103761
                  imonthdum7 |   .0337298   .0186939     1.80   0.071    -.0029318    .0703914
                  imonthdum8 |   .0350047   .0328047     1.07   0.286    -.0293304    .0993397
                  imonthdum9 |    .093731   .0422887     2.22   0.027     .0107963    .1766657
                 imonthdum10 |    .073652   .0395286     1.86   0.063    -.0038697    .1511738
                 imonthdum11 |  -.0016471   .0242342    -0.07   0.946    -.0491741    .0458799
                 imonthdum12 |   .0395155   .0249358     1.58   0.113    -.0093875    .0884185
                 imonthdum13 |   .0425798   .0215221     1.98   0.048     .0003716     .084788
                 imonthdum14 |  -.0177426   .0241913    -0.73   0.463    -.0651855    .0297003
                 imonthdum15 |   .0178154   .0220042     0.81   0.418    -.0253382    .0609689
                 imonthdum16 |  -.0124198   .0253948    -0.49   0.625     -.062223    .0373834
                 imonthdum17 |   .0011487   .0194773     0.06   0.953    -.0370492    .0393467
                 imonthdum18 |   .0091985   .0242448     0.38   0.704    -.0383494    .0567463
                 imonthdum19 |  -.0114632   .0202906    -0.56   0.572    -.0512562    .0283298
                 imonthdum20 |  -.0071702   .0209905    -0.34   0.733    -.0483357    .0339953
        ZLNpc_new_cases_7day |   .0105404   .0037927     2.78   0.006     .0031024    .0179785
               out_workforce |  -.0235183   .0229442    -1.03   0.305    -.0685155    .0214788
                    employed |  -.0266077   .0206308    -1.29   0.197    -.0670679    .0138525
                      income |  -.0020442   .0033166    -0.62   0.538    -.0085486    .0044603
Yc4_restrictionsongatherings |  -.0031198   .0112961    -0.28   0.782    -.0252732    .0190336
  Yc6_stayathomerequirements |   .0075286   .0080786     0.93   0.351    -.0083147    .0233719
                       _cons |   .1308635   .0254262     5.15   0.000     .0809987    .1807283
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       255           1         254     |
         pid |     15909       15909           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe v_worry_ill dem indep_third dmonthdum2 dmonthdum4-dmonthdum20 imonthdum2 imonthdum4-imonthdum20 $controls_fe_model Yc
> 4_restrictionsongatherings Yc6_stayathomerequirements $controls_main_model  [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 131 singleton observations)
(MWFE estimator converged in 8 iterations)
note: dmonthdum2 omitted because of collinearity
note: imonthdum2 omitted because of collinearity

HDFE Linear regression                            Number of obs   =    109,644
Absorbing 2 HDFE groups                           F(  54,   2461) =      16.55
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1380
                                                  Adj R-squared   =     0.1156
                                                  Within R-sq.    =     0.0374
Number of clusters (ctyfip)  =      2,462         Root MSE        =     0.2851

                                             (Std. err. adjusted for 2,462 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |    .103115   .0129591     7.96   0.000     .0777032    .1285268
                 indep_third |   .0389998    .012167     3.21   0.001     .0151413    .0628584
                  dmonthdum2 |          0  (omitted)
                  dmonthdum4 |   .0069722   .0156471     0.45   0.656    -.0237106     .037655
                  dmonthdum5 |  -.0013594   .0150996    -0.09   0.928    -.0309686    .0282498
                  dmonthdum6 |   .0691194   .0160972     4.29   0.000     .0375539    .1006849
                  dmonthdum7 |   .0579764   .0180506     3.21   0.001     .0225806    .0933723
                  dmonthdum8 |   .0390206   .0275949     1.41   0.157    -.0150911    .0931323
                  dmonthdum9 |   .0486803   .0286889     1.70   0.090    -.0075766    .1049372
                 dmonthdum10 |   .0903861   .0329542     2.74   0.006     .0257652    .1550069
                 dmonthdum11 |   .0462882   .0210614     2.20   0.028     .0049882    .0875881
                 dmonthdum12 |   .0410974   .0169871     2.42   0.016      .007787    .0744079
                 dmonthdum13 |   .0250941   .0203023     1.24   0.217    -.0147172    .0649054
                 dmonthdum14 |  -.0269569   .0166616    -1.62   0.106    -.0596292    .0057154
                 dmonthdum15 |  -.0498023    .015442    -3.23   0.001     -.080083   -.0195217
                 dmonthdum16 |  -.0826014   .0157764    -5.24   0.000    -.1135378   -.0516651
                 dmonthdum17 |  -.0831173   .0145607    -5.71   0.000    -.1116697   -.0545649
                 dmonthdum18 |  -.0779153   .0172876    -4.51   0.000    -.1118149   -.0440156
                 dmonthdum19 |  -.0348305   .0184854    -1.88   0.060    -.0710791    .0014181
                 dmonthdum20 |  -.0490263   .0161892    -3.03   0.002    -.0807723   -.0172804
                  imonthdum2 |          0  (omitted)
                  imonthdum4 |    .004094   .0154025     0.27   0.790    -.0261092    .0342972
                  imonthdum5 |   .0133649   .0145028     0.92   0.357     -.015074    .0418038
                  imonthdum6 |   .0531646   .0166758     3.19   0.001     .0204646    .0858646
                  imonthdum7 |   .0614956   .0169105     3.64   0.000     .0283354    .0946558
                  imonthdum8 |   .0130088    .026619     0.49   0.625    -.0391892    .0652067
                  imonthdum9 |   .0505951    .028984     1.75   0.081    -.0062405    .1074307
                 imonthdum10 |    .069804   .0287325     2.43   0.015     .0134616    .1261464
                 imonthdum11 |    .010576   .0200895     0.53   0.599    -.0288181      .04997
                 imonthdum12 |   .0240547   .0175269     1.37   0.170    -.0103143    .0584237
                 imonthdum13 |   .0240794    .018322     1.31   0.189    -.0118488    .0600076
                 imonthdum14 |   .0054821   .0149358     0.37   0.714    -.0238058    .0347701
                 imonthdum15 |   .0054095   .0144653     0.37   0.708    -.0229559     .033775
                 imonthdum16 |  -.0307058   .0134028    -2.29   0.022    -.0569877   -.0044239
                 imonthdum17 |    -.02394   .0136427    -1.75   0.079    -.0506924    .0028123
                 imonthdum18 |  -.0071474   .0158544    -0.45   0.652    -.0382367    .0239419
                 imonthdum19 |  -.0295399   .0163109    -1.81   0.070    -.0615244    .0024445
                 imonthdum20 |   .0156866   .0163175     0.96   0.336     -.016311    .0476841
        ZLNpc_new_cases_7day |   .0112966   .0028396     3.98   0.000     .0057283    .0168649
               out_workforce |  -.0308401    .012215    -2.52   0.012    -.0547928   -.0068873
                    employed |  -.0346105   .0116804    -2.96   0.003    -.0575149    -.011706
                      income |  -.0053599   .0011368    -4.72   0.000    -.0075891   -.0031308
Yc4_restrictionsongatherings |  -.0030617   .0066922    -0.46   0.647    -.0161847    .0100612
  Yc6_stayathomerequirements |   .0012233   .0057667     0.21   0.832    -.0100847    .0125314
                        male |   -.039762   .0053375    -7.45   0.000    -.0502284   -.0292956
                       age10 |  -.0011652   .0023142    -0.50   0.615    -.0057031    .0033728
                  age_group4 |  -.0273192   .0091117    -3.00   0.003    -.0451866   -.0094518
             live_w_children |   .0012598   .0054902     0.23   0.819     -.009506    .0120257
                     somecol |   .0124757   .0062327     2.00   0.045     .0002538    .0246977
                          ba |   .0023546   .0075365     0.31   0.755     -.012424    .0171331
                        grad |   .0114122   .0076626     1.49   0.137    -.0036137    .0264381
                     AmerInd |   .0206773   .0309216     0.67   0.504    -.0399578    .0813124
                       Asian |   .0293032   .0314115     0.93   0.351    -.0322924    .0908988
                       Black |  -.0086869   .0095837    -0.91   0.365    -.0274799    .0101061
                        Hisp |   .0188219   .0090721     2.07   0.038     .0010321    .0366117
                 Multiracial |   .0232601   .0128506     1.81   0.070     -.001939    .0484593
                       _cons |    .124837   .0175553     7.11   0.000     .0904123    .1592616
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       265           1         264     |
      ctyfip |      2462        2462           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Worry", replace) ///
> title("Very worried about COVID (base month April 2020)") xtitle("Pandemic Month")
(file Worry.gph not found)
file Worry.gph saved

. 
. *Mostly Remote
. 
. estimates clear

. reghdfe mostly_remote dem indep_third dmonthdum5-dmonthdum20 imonthdum5-imonthdum20  ZLNpc_new_cases_7day  live_w_children in
> come Yc4_restrictionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing  [aw=WEIGHT]  if (minmonthmostly_remote==4 
> | minmonthmostly_remote==5)  &  employed==1, a(time ctyfip pid) vce(cl ctyfip)
(dropped 2028 singleton observations)
(MWFE estimator converged in 14 iterations)
note: dem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: indep_third is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: live_w_children is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     21,011
Absorbing 3 HDFE groups                           F(  37,   1420) =       1.06
Statistics robust to heteroskedasticity           Prob > F        =     0.3728
                                                  R-squared       =     0.8037
                                                  Adj R-squared   =     0.6683
                                                  Within R-sq.    =     0.0051
Number of clusters (ctyfip)  =      1,421         Root MSE        =     0.2877

                                             (Std. err. adjusted for 1,421 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |          0  (omitted)
                 indep_third |          0  (omitted)
                  dmonthdum5 |  -.0054818   .0296522    -0.18   0.853    -.0636487     .052685
                  dmonthdum6 |   .0226464   .0298114     0.76   0.448    -.0358328    .0811255
                  dmonthdum7 |   .0387202   .0359872     1.08   0.282    -.0318736     .109314
                  dmonthdum8 |  -.0400694   .0586593    -0.68   0.495    -.1551376    .0749988
                  dmonthdum9 |  -.0000389   .0627046    -0.00   1.000    -.1230425    .1229646
                 dmonthdum10 |   .0758464    .076588     0.99   0.322    -.0743913    .2260842
                 dmonthdum11 |  -.0334205    .038122    -0.88   0.381     -.108202    .0413609
                 dmonthdum12 |  -.0567565   .0422699    -1.34   0.180    -.1396746    .0261616
                 dmonthdum13 |  -.0536292    .040436    -1.33   0.185    -.1329498    .0256914
                 dmonthdum14 |   .0329223   .0455166     0.72   0.470    -.0563647    .1222093
                 dmonthdum15 |  -.0945094   .0506738    -1.87   0.062    -.1939129    .0048941
                 dmonthdum16 |  -.0584763   .0447189    -1.31   0.191    -.1461986     .029246
                 dmonthdum17 |   .0065429   .0477876     0.14   0.891     -.087199    .1002849
                 dmonthdum18 |  -.0048677   .0554468    -0.09   0.930    -.1136342    .1038988
                 dmonthdum19 |   .0229535    .056402     0.41   0.684    -.0876867    .1335936
                 dmonthdum20 |  -.0871642   .0479227    -1.82   0.069     -.181171    .0068427
                  imonthdum5 |   -.005457   .0334546    -0.16   0.870    -.0710828    .0601687
                  imonthdum6 |  -.0189141   .0328177    -0.58   0.564    -.0832904    .0454622
                  imonthdum7 |  -.0131409   .0331921    -0.40   0.692    -.0782517    .0519698
                  imonthdum8 |  -.0447332    .067814    -0.66   0.510    -.1777595    .0882931
                  imonthdum9 |  -.1068486    .061636    -1.73   0.083     -.227756    .0140588
                 imonthdum10 |   .0512271   .0725341     0.71   0.480    -.0910584    .1935126
                 imonthdum11 |   -.034786   .0423848    -0.82   0.412    -.1179295    .0483576
                 imonthdum12 |  -.0570998   .0463593    -1.23   0.218    -.1480399    .0338404
                 imonthdum13 |    .003554   .0463704     0.08   0.939    -.0874079    .0945159
                 imonthdum14 |   .0262069   .0435536     0.60   0.547    -.0592294    .1116432
                 imonthdum15 |  -.0471139   .0562808    -0.84   0.403    -.1575164    .0632885
                 imonthdum16 |   -.036002   .0492776    -0.73   0.465    -.1326667    .0606627
                 imonthdum17 |   .0312891   .0477946     0.65   0.513    -.0624665    .1250448
                 imonthdum18 |   .0690585   .0544746     1.27   0.205    -.0378008    .1759178
                 imonthdum19 |   .0013673   .0643881     0.02   0.983    -.1249387    .1276733
                 imonthdum20 |  -.0831395   .0493127    -1.69   0.092    -.1798731    .0135942
        ZLNpc_new_cases_7day |  -.0019648   .0074986    -0.26   0.793    -.0166743    .0127447
             live_w_children |          0  (omitted)
                      income |  -.0022091   .0070427    -0.31   0.754    -.0160242    .0116061
Yc4_restrictionsongatherings |   -.010201   .0162615    -0.63   0.531       -.0421    .0216981
  Yc6_stayathomerequirements |  -.0062772   .0128178    -0.49   0.624     -.031421    .0188667
        Yc2_workplaceclosing |   .0023456   .0123237     0.19   0.849    -.0218291    .0265204
                       _cons |   .5077777   .0474123    10.71   0.000      .414772    .6007833
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       238           1         237     |
      ctyfip |      1421        1421           0    *|
         pid |      6885        6885           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe mostly_remote dem indep_third dmonthdum5-dmonthdum20 imonthdum5-imonthdum20 ZLNpc_new_cases_7day  live_w_children inc
> ome Yc4_restrictionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing  $controls_main_model  if  employed==1 [aw=W
> EIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 248 singleton observations)
(MWFE estimator converged in 8 iterations)
note: live_w_children omitted because of collinearity

HDFE Linear regression                            Number of obs   =     50,033
Absorbing 2 HDFE groups                           F(  51,   1956) =      40.88
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3209
                                                  Adj R-squared   =     0.2889
                                                  Within R-sq.    =     0.1255
Number of clusters (ctyfip)  =      1,957         Root MSE        =     0.4185

                                             (Std. err. adjusted for 1,957 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .1334046   .0224473     5.94   0.000     .0893815    .1774276
                 indep_third |   .0826735   .0229015     3.61   0.000     .0377595    .1275875
                  dmonthdum5 |   .0068336   .0278572     0.25   0.806    -.0477993    .0614665
                  dmonthdum6 |   .0320586   .0270849     1.18   0.237    -.0210597    .0851769
                  dmonthdum7 |   .0184945   .0322641     0.57   0.567    -.0447811    .0817702
                  dmonthdum8 |   .1045968   .0552989     1.89   0.059    -.0038541    .2130477
                  dmonthdum9 |  -.0273802    .064225    -0.43   0.670    -.1533369    .0985765
                 dmonthdum10 |    .058204   .0552296     1.05   0.292    -.0501111    .1665191
                 dmonthdum11 |   .0367911   .0368095     1.00   0.318    -.0353988    .1089811
                 dmonthdum12 |  -.0323125   .0355967    -0.91   0.364     -.102124    .0374989
                 dmonthdum13 |  -.0336674   .0351398    -0.96   0.338    -.1025828     .035248
                 dmonthdum14 |  -.0097853    .037819    -0.26   0.796    -.0839551    .0643845
                 dmonthdum15 |  -.0748615   .0389635    -1.92   0.055    -.1512759    .0015529
                 dmonthdum16 |  -.0836078   .0360265    -2.32   0.020    -.1542621   -.0129535
                 dmonthdum17 |   -.029336    .035144    -0.83   0.404    -.0982597    .0395876
                 dmonthdum18 |  -.0450378   .0375358    -1.20   0.230    -.1186522    .0285765
                 dmonthdum19 |  -.0060055   .0381193    -0.16   0.875    -.0807642    .0687531
                 dmonthdum20 |  -.0939894   .0363023    -2.59   0.010    -.1651846   -.0227942
                  imonthdum5 |   .0051058   .0322104     0.16   0.874    -.0580646    .0682762
                  imonthdum6 |  -.0136339   .0302628    -0.45   0.652    -.0729846    .0457168
                  imonthdum7 |   .0064267   .0366308     0.18   0.861    -.0654129    .0782663
                  imonthdum8 |   .0761419   .0585212     1.30   0.193    -.0386287    .1909125
                  imonthdum9 |  -.0261586   .0622853    -0.42   0.675    -.1483112    .0959939
                 imonthdum10 |   -.024046   .0530553    -0.45   0.650    -.1280969    .0800049
                 imonthdum11 |  -.0228977   .0366238    -0.63   0.532    -.0947234     .048928
                 imonthdum12 |  -.0809949   .0337774    -2.40   0.017    -.1472383   -.0147515
                 imonthdum13 |  -.0354087   .0362052    -0.98   0.328    -.1064136    .0355962
                 imonthdum14 |  -.0329084   .0376791    -0.87   0.383    -.1068038    .0409869
                 imonthdum15 |  -.0218846   .0381621    -0.57   0.566    -.0967272    .0529581
                 imonthdum16 |  -.0853022   .0369476    -2.31   0.021     -.157763   -.0128414
                 imonthdum17 |   .0164928   .0356977     0.46   0.644    -.0535167    .0865022
                 imonthdum18 |  -.0119732   .0428033    -0.28   0.780     -.095918    .0719717
                 imonthdum19 |  -.0058384   .0365078    -0.16   0.873    -.0774367    .0657598
                 imonthdum20 |  -.0391435   .0342684    -1.14   0.253    -.1063499    .0280629
        ZLNpc_new_cases_7day |  -.0014307   .0055912    -0.26   0.798     -.012396    .0095346
             live_w_children |  -.0391791   .0107084    -3.66   0.000    -.0601802    -.018178
                      income |    .035953   .0025502    14.10   0.000     .0309516    .0409545
Yc4_restrictionsongatherings |    .011289   .0123075     0.92   0.359    -.0128482    .0354262
  Yc6_stayathomerequirements |   .0047261   .0118506     0.40   0.690     -.018515    .0279673
        Yc2_workplaceclosing |  -.0062244   .0090209    -0.69   0.490     -.023916    .0114671
                        male |  -.0974661   .0107006    -9.11   0.000    -.1184519   -.0764803
                       age10 |  -.0179436    .004659    -3.85   0.000    -.0270807   -.0088065
                  age_group4 |    .014274   .0197689     0.72   0.470    -.0244964    .0530444
             live_w_children |          0  (omitted)
                     somecol |   .0566756   .0148088     3.83   0.000     .0276329    .0857184
                          ba |   .2346597   .0175617    13.36   0.000     .2002182    .2691013
                        grad |   .2505116   .0166333    15.06   0.000     .2178907    .2831325
                     AmerInd |  -.0971592   .0635867    -1.53   0.127    -.2218641    .0275456
                       Asian |   .0979712   .0513622     1.91   0.057    -.0027593    .1987016
                       Black |   .0236226   .0179013     1.32   0.187     -.011485    .0587303
                        Hisp |  -.0165678   .0201186    -0.82   0.410    -.0560239    .0228883
                 Multiracial |  -.0532882   .0262661    -2.03   0.043    -.1048007   -.0017757
                       _cons |   .1522467   .0315723     4.82   0.000     .0903278    .2141656
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       248           1         247     |
      ctyfip |      1957        1957           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Remote", replace) ///
> title("Mostly working remote (base month May 2020)") xtitle("Pandemic Month")
(file Remote.gph not found)
file Remote.gph saved

. 
. grc1leg MostlyIsolate.gph Mask.gph Worry.gph Remote.gph   ///
> , imargin(2 2 2 2) row(2) col(2) legendfrom(MostlyIsolate.gph) iscale(*.75) plotregion(color(white)) graphregion(color(white)
> )  

. graph export "figures\Figure S11.png", replace width(2200) height(1600)
file figures\Figure S11.png saved as PNG format

. 
. * Delete the intermediate files
. erase MostlyIsolate.gph

. erase Mask.gph

. erase Worry.gph

. erase Remote.gph

. 
. 
. 
. ******************
. *** Figure S12 ***
. ******************
. 
. *Change in Partisan Gap in COVID-19 Responses, with Fixed Effects for Date × County
. 
. *Note that these regressions can take several minutes to run
. 
. clear

. use "data_gallup.dta"

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(4,143 real changes made)
(3,759 real changes made)
(3,905 real changes made)
(3,731 real changes made)
(3,572 real changes made)
(4,843 real changes made)
(3,475 real changes made)
(3,553 real changes made)
(4,034 real changes made)

. egen minmonthvac=min(month_number) if vaccinated!=., by(pid)
(264 missing values generated)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(30,507 missing values generated)

. egen minmonthisol=min(month_number) if Mostly_Isol!=., by(pid)
(5,890 missing values generated)

. egen minmonthworry=min(month_number) if v_worry_ill!=., by(pid)
(35,223 missing values generated)

. egen minmonthmostly_remote=min(month_number) if mostly_remote!=., by(pid)
(108,466 missing values generated)

. 
. 
. *Mostly Isolate
. 
. estimates clear

. reghdfe Mostly_Isol  dmonthdum3-dmonthdum20 imonthdum3-imonthdum20  Yc4_restrictionsongatherings Yc6_stayathomerequirements $
> controls_fe_model [aw=WEIGHT]  if minmonthisol==3 ,  a(time pid) vce(cl ctyfip)
(dropped 1672 singleton observations)
(MWFE estimator converged in 11 iterations)

HDFE Linear regression                            Number of obs   =     55,026
Absorbing 2 HDFE groups                           F(  42,   1939) =       4.43
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5851
                                                  Adj R-squared   =     0.4300
                                                  Within R-sq.    =     0.0121
Number of clusters (ctyfip)  =      1,940         Root MSE        =     0.3773

                                             (Std. err. adjusted for 1,940 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  dmonthdum3 |   .0643316   .0259088     2.48   0.013     .0135196    .1151436
                  dmonthdum4 |   .1340196   .0327533     4.09   0.000     .0697841    .1982551
                  dmonthdum5 |   .1355868   .0316267     4.29   0.000     .0735609    .1976128
                  dmonthdum6 |   .1376109   .0334957     4.11   0.000     .0719195    .2033023
                  dmonthdum7 |   .1936218    .039421     4.91   0.000     .1163099    .2709337
                  dmonthdum8 |   .1534357   .0758807     2.02   0.043     .0046194     .302252
                  dmonthdum9 |    .192144   .0647728     2.97   0.003     .0651123    .3191757
                 dmonthdum10 |   .1052079   .0796855     1.32   0.187    -.0510704    .2614863
                 dmonthdum11 |   .1555771   .0416197     3.74   0.000     .0739531    .2372011
                 dmonthdum12 |   .2157118   .0375271     5.75   0.000      .142114    .2893096
                 dmonthdum13 |   .1347023    .040475     3.33   0.001     .0553233    .2140814
                 dmonthdum14 |   .2344896   .0436027     5.38   0.000     .1489765    .3200027
                 dmonthdum15 |   .0583325   .0484829     1.20   0.229    -.0367515    .1534166
                 dmonthdum16 |   .0834979   .0457378     1.83   0.068    -.0062024    .1731983
                 dmonthdum17 |   .0117849   .0410141     0.29   0.774    -.0686515    .0922213
                 dmonthdum18 |   .0006119   .0477811     0.01   0.990     -.093096    .0943197
                 dmonthdum19 |   .1497238   .0482257     3.10   0.002     .0551441    .2443035
                 dmonthdum20 |   -.038568   .0482082    -0.80   0.424    -.1331135    .0559774
                  imonthdum3 |   .0191383   .0273757     0.70   0.485    -.0345506    .0728273
                  imonthdum4 |   .0810192   .0338512     2.39   0.017     .0146306    .1474078
                  imonthdum5 |   .0533874    .033388     1.60   0.110    -.0120927    .1188675
                  imonthdum6 |   .0795749   .0331754     2.40   0.017     .0145117    .1446382
                  imonthdum7 |   .1345128    .039098     3.44   0.001     .0578342    .2111913
                  imonthdum8 |   .1779789   .0753074     2.36   0.018     .0302868    .3256709
                  imonthdum9 |    .244177   .0695332     3.51   0.000     .1078093    .3805447
                 imonthdum10 |  -.0156744   .0870892    -0.18   0.857    -.1864728     .155124
                 imonthdum11 |   .1074047    .048954     2.19   0.028     .0113967    .2034127
                 imonthdum12 |   .1042296   .0367647     2.84   0.005      .032127    .1763322
                 imonthdum13 |   .1270202   .0420933     3.02   0.003     .0444673    .2095731
                 imonthdum14 |   .1338451   .0479809     2.79   0.005     .0397456    .2279447
                 imonthdum15 |   .0525707   .0551307     0.95   0.340    -.0555511    .1606925
                 imonthdum16 |   .0819115   .0437771     1.87   0.061    -.0039435    .1677666
                 imonthdum17 |   .0484318   .0356559     1.36   0.175    -.0214962    .1183597
                 imonthdum18 |   .0690343   .0513014     1.35   0.179    -.0315775    .1696461
                 imonthdum19 |   .1315762   .0463153     2.84   0.005     .0407431    .2224092
                 imonthdum20 |  -.0274507   .0447635    -0.61   0.540    -.1152403     .060339
Yc4_restrictionsongatherings |   .0049883   .0147322     0.34   0.735    -.0239044     .033881
  Yc6_stayathomerequirements |   .0077395    .011834     0.65   0.513    -.0154693    .0309483
        ZLNpc_new_cases_7day |   .0209953   .0058225     3.61   0.000     .0095762    .0324143
               out_workforce |   .0019856   .0382277     0.05   0.959    -.0729861    .0769573
                    employed |  -.0945824   .0322107    -2.94   0.003    -.1577537    -.031411
                      income |  -.0030138   .0061779    -0.49   0.626    -.0151298    .0091022
                       _cons |   .5323141   .0525939    10.12   0.000     .4291676    .6354607
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       274           1         273     |
         pid |     14659       14659           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe Mostly_Isol dem indep_third dmonthdum3-dmonthdum20 imonthdum3-imonthdum20 Yc4_restrictionsongatherings Yc6_stayathome
> requirements $controls_main_model $controls_fe_model  [aw=WEIGHT],  a(time ctyfip cty_x_time) vce(cl ctyfip)
(dropped 56769 singleton observations)
(MWFE estimator converged in 876 iterations)

HDFE Linear regression                            Number of obs   =     81,797
Absorbing 3 HDFE groups                           F(  56,   1229) =      25.24
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6524
                                                  Adj R-squared   =     0.4835
                                                  Within R-sq.    =     0.0670
Number of clusters (ctyfip)  =      1,230         Root MSE        =     0.3584

                                             (Std. err. adjusted for 1,230 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .1073122   .0311928     3.44   0.001     .0461151    .1685093
                 indep_third |   .0986982   .0369206     2.67   0.008     .0262638    .1711326
                  dmonthdum3 |   .0534482   .0380691     1.40   0.161    -.0212395    .1281358
                  dmonthdum4 |   .1311646   .0489839     2.68   0.008     .0350633     .227266
                  dmonthdum5 |   .1299359   .0457976     2.84   0.005     .0400858     .219786
                  dmonthdum6 |    .207517   .0491857     4.22   0.000     .1110198    .3040143
                  dmonthdum7 |   .1154959   .0520084     2.22   0.027     .0134608    .2175311
                  dmonthdum8 |   .0955196   .1121643     0.85   0.395    -.1245352    .3155743
                  dmonthdum9 |   .1591622   .1045051     1.52   0.128     -.045866    .3641904
                 dmonthdum10 |   .1217561   .1216433     1.00   0.317    -.1168954    .3604076
                 dmonthdum11 |    .143106   .0552167     2.59   0.010     .0347766    .2514355
                 dmonthdum12 |   .2381855   .0516681     4.61   0.000     .1368181    .3395529
                 dmonthdum13 |   .1944313   .0507801     3.83   0.000      .094806    .2940566
                 dmonthdum14 |   .1798176   .0544712     3.30   0.001     .0729508    .2866843
                 dmonthdum15 |   .0216439   .0517342     0.42   0.676    -.0798532     .123141
                 dmonthdum16 |   .0638554   .0473103     1.35   0.177    -.0289624    .1566732
                 dmonthdum17 |   .0724054   .0508765     1.42   0.155     -.027409    .1722199
                 dmonthdum18 |  -.0288428   .0477118    -0.60   0.546    -.1224484    .0647627
                 dmonthdum19 |   .0977691   .0464162     2.11   0.035     .0067054    .1888328
                 dmonthdum20 |   .0223852   .0495047     0.45   0.651    -.0747379    .1195083
                  imonthdum3 |   .0251216   .0373372     0.67   0.501    -.0481301    .0983734
                  imonthdum4 |   .0251945   .0533818     0.47   0.637     -.079535     .129924
                  imonthdum5 |   .0826163   .0567524     1.46   0.146    -.0287259    .1939586
                  imonthdum6 |   .0901918   .0536746     1.68   0.093    -.0151121    .1954957
                  imonthdum7 |   .0032947   .0633863     0.05   0.959    -.1210626     .127652
                  imonthdum8 |  -.0335432    .111061    -0.30   0.763    -.2514335     .184347
                  imonthdum9 |    .117619   .1260725     0.93   0.351    -.1297222    .3649602
                 imonthdum10 |   .0272807   .1189401     0.23   0.819    -.2060673    .2606288
                 imonthdum11 |   .0957894   .0692337     1.38   0.167    -.0400399    .2316187
                 imonthdum12 |   .0698504    .065936     1.06   0.290    -.0595093      .19921
                 imonthdum13 |   .0737152   .0590027     1.25   0.212    -.0420421    .1894725
                 imonthdum14 |   .0547286   .0542767     1.01   0.313    -.0517566    .1612138
                 imonthdum15 |    .071109   .0586257     1.21   0.225    -.0439086    .1861265
                 imonthdum16 |  -.0044564   .0468199    -0.10   0.924    -.0963122    .0873994
                 imonthdum17 |   .0153549   .0464944     0.33   0.741    -.0758623     .106572
                 imonthdum18 |  -.0043217   .0624601    -0.07   0.945    -.1268618    .1182185
                 imonthdum19 |   .0342522   .0596666     0.57   0.566    -.0828075     .151312
                 imonthdum20 |  -.0237447   .0490958    -0.48   0.629    -.1200654    .0725761
Yc4_restrictionsongatherings |   .0060099   .0901253     0.07   0.947    -.1708067    .1828264
  Yc6_stayathomerequirements |  -.0507171   .0614014    -0.83   0.409    -.1711802    .0697461
                        male |  -.0408918   .0083466    -4.90   0.000     -.057267   -.0245165
                       age10 |    -.02036   .0052379    -3.89   0.000    -.0306363   -.0100838
                  age_group4 |   .0050886   .0174445     0.29   0.771    -.0291356    .0393129
             live_w_children |  -.0328781   .0102057    -3.22   0.001    -.0529005   -.0128557
                     somecol |   .0253278   .0156767     1.62   0.106    -.0054283    .0560839
                          ba |   .0706202   .0173737     4.06   0.000     .0365348    .1047056
                        grad |   .0881949   .0182112     4.84   0.000     .0524664    .1239235
                     AmerInd |   .0212186   .0469341     0.45   0.651    -.0708612    .1132984
                       Asian |   .0115198   .0449812     0.26   0.798    -.0767286    .0997683
                       Black |  -.0509874   .0184664    -2.76   0.006    -.0872165   -.0147584
                        Hisp |   .0122735    .018831     0.65   0.515     -.024671    .0492181
                 Multiracial |   .0080422    .026168     0.31   0.759    -.0432968    .0593811
        ZLNpc_new_cases_7day |   .5844052   .2192796     2.67   0.008     .1542015    1.014609
               out_workforce |  -.0127123   .0260118    -0.49   0.625    -.0637448    .0383202
                    employed |  -.1663902   .0247261    -6.73   0.000    -.2149002   -.1178803
                      income |    .006535    .002587     2.53   0.012     .0014596    .0116104
                       _cons |    .477083   .0995404     4.79   0.000     .2817951    .6723709
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       258           1         257     |
      ctyfip |      1230        1230           0    *|
  cty_x_time |     25285          73       25212     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("MostlyIsolate", replace) ///
> title("Mostly Isolating (base month March 2020)") xtitle("Pandemic Month")
(file MostlyIsolate.gph not found)
file MostlyIsolate.gph saved

. 
. 
. *Worn Masks
. 
. estimates clear

. reghdfe worn_mask dem indep_third dmonthdum4-dmonthdum20 imonthdum4-imonthdum20  $controls_fe_model  Y3h6_facialcoverings [aw
> =WEIGHT]  if minmonthmask==4  , a(time pid) vce(cl ctyfip)
(dropped 3832 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     65,975
Absorbing 2 HDFE groups                           F(  41,   2149) =       8.55
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6222
                                                  Adj R-squared   =     0.4462
                                                  Within R-sq.    =     0.0211
Number of clusters (ctyfip)  =      2,150         Root MSE        =     0.3040

                                     (Std. err. adjusted for 2,150 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |  -.0711372   .0268234    -2.65   0.008    -.1237397   -.0185347
         indep_third |   -.075222    .025158    -2.99   0.003    -.1245585   -.0258855
          dmonthdum4 |   .0593379   .0274246     2.16   0.031     .0055563    .1131195
          dmonthdum5 |   .0869463   .0244685     3.55   0.000      .038962    .1349307
          dmonthdum6 |   -.014265   .0225365    -0.63   0.527    -.0584605    .0299306
          dmonthdum7 |  -.0543597   .0239624    -2.27   0.023    -.1013516   -.0073678
          dmonthdum8 |  -.0816948   .0410876    -1.99   0.047    -.1622703   -.0011193
          dmonthdum9 |  -.0074517   .0418183    -0.18   0.859    -.0894603    .0745569
         dmonthdum10 |  -.0282842   .0323174    -0.88   0.382    -.0916609    .0350924
         dmonthdum11 |    .015155   .0287092     0.53   0.598    -.0411457    .0714557
         dmonthdum12 |  -.0745412    .027784    -2.68   0.007    -.1290274   -.0200549
         dmonthdum13 |  -.0103923   .0316237    -0.33   0.742    -.0724086     .051624
         dmonthdum14 |  -.0227798   .0293281    -0.78   0.437    -.0802942    .0347346
         dmonthdum15 |   .0195452   .0332391     0.59   0.557     -.045639    .0847293
         dmonthdum16 |   .1268244   .0361008     3.51   0.000     .0560283    .1976206
         dmonthdum17 |   .2102053    .033571     6.26   0.000     .1443702    .2760404
         dmonthdum18 |   .2168345   .0452687     4.79   0.000     .1280595    .3056094
         dmonthdum19 |   .2504275   .0385633     6.49   0.000     .1748022    .3260528
         dmonthdum20 |   .2305409   .0321544     7.17   0.000     .1674838    .2935979
          imonthdum4 |   .0664256   .0319776     2.08   0.038     .0037154    .1291358
          imonthdum5 |   .0495043   .0265222     1.87   0.062    -.0025077    .1015162
          imonthdum6 |   .0292369   .0259159     1.13   0.259    -.0215859    .0800597
          imonthdum7 |  -.0178958   .0279308    -0.64   0.522      -.07267    .0368783
          imonthdum8 |  -.0942882   .0458526    -2.06   0.040    -.1842082   -.0043681
          imonthdum9 |  -.0228955   .0523845    -0.44   0.662    -.1256251     .079834
         imonthdum10 |   .0440287   .0412177     1.07   0.286    -.0368021    .1248595
         imonthdum11 |   .0976878   .0368827     2.65   0.008     .0253583    .1700173
         imonthdum12 |  -.0210032   .0301904    -0.70   0.487    -.0802086    .0382021
         imonthdum13 |   .0316018   .0371041     0.85   0.394    -.0411618    .1043654
         imonthdum14 |    .013345   .0333238     0.40   0.689    -.0520053    .0786953
         imonthdum15 |   .0463099   .0384767     1.20   0.229    -.0291455    .1217653
         imonthdum16 |    .091246    .041951     2.18   0.030     .0089772    .1735147
         imonthdum17 |   .0669514   .0418727     1.60   0.110    -.0151638    .1490667
         imonthdum18 |   .1159992   .0509111     2.28   0.023     .0161589    .2158394
         imonthdum19 |   .1311693   .0458321     2.86   0.004     .0412893    .2210492
         imonthdum20 |   .0904038   .0378267     2.39   0.017      .016223    .1645846
ZLNpc_new_cases_7day |   .0361017    .005158     7.00   0.000     .0259864     .046217
       out_workforce |   .0033903   .0272244     0.12   0.901    -.0499986    .0567791
            employed |   .0196658   .0236751     0.83   0.406    -.0267626    .0660942
              income |  -.0049402   .0044335    -1.11   0.265    -.0136345    .0037542
Y3h6_facialcoverings |   .0180211   .0092622     1.95   0.052    -.0001427     .036185
               _cons |   .8212228   .0368429    22.29   0.000     .7489713    .8934743
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       268           1         267     |
         pid |     20664       20664           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe worn_mask dem indep_third dmonthdum4-dmonthdum20 imonthdum4-imonthdum20 $controls_fe_model  Y3h6_facialcoverings $con
> trols_main_model [aw=WEIGHT], a(time ctyfip cty_x_time) vce(cl ctyfip)
(dropped 50765 singleton observations)
(MWFE estimator converged in 978 iterations)

HDFE Linear regression                            Number of obs   =     67,792
Absorbing 3 HDFE groups                           F(  53,   1161) =      17.50
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6761
                                                  Adj R-squared   =     0.5121
                                                  Within R-sq.    =     0.0918
Number of clusters (ctyfip)  =      1,162         Root MSE        =     0.2617

                                     (Std. err. adjusted for 1,162 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |   .1697636   .0258012     6.58   0.000     .1191413    .2203859
         indep_third |   .0904268   .0308524     2.93   0.003     .0298941    .1509596
          dmonthdum4 |   .0136054   .0368688     0.37   0.712    -.0587314    .0859422
          dmonthdum5 |   .0046135   .0376979     0.12   0.903    -.0693501     .078577
          dmonthdum6 |  -.0438948   .0377078    -1.16   0.245    -.1178779    .0300882
          dmonthdum7 |  -.0753549    .040055    -1.88   0.060    -.1539431    .0032333
          dmonthdum8 |  -.1130271   .0418492    -2.70   0.007    -.1951356   -.0309185
          dmonthdum9 |     .06155   .0775741     0.79   0.428    -.0906511    .2137511
         dmonthdum10 |   .0466878   .0839612     0.56   0.578    -.1180449    .2114205
         dmonthdum11 |  -.0147342   .0471171    -0.31   0.755    -.1071784      .07771
         dmonthdum12 |  -.0607116   .0353067    -1.72   0.086    -.1299837    .0085604
         dmonthdum13 |  -.0558776   .0421159    -1.33   0.185    -.1385093    .0267542
         dmonthdum14 |  -.0331791   .0421995    -0.79   0.432    -.1159748    .0496167
         dmonthdum15 |  -.0103508   .0454598    -0.23   0.820    -.0995434    .0788417
         dmonthdum16 |   .1234282   .0497046     2.48   0.013     .0259073    .2209491
         dmonthdum17 |   .1849483   .0411356     4.50   0.000     .1042399    .2656568
         dmonthdum18 |   .2737641    .056034     4.89   0.000     .1638248    .3837033
         dmonthdum19 |   .3276661   .0527812     6.21   0.000     .2241088    .4312233
         dmonthdum20 |   .2428182   .0404512     6.00   0.000     .1634525    .3221839
          imonthdum4 |  -.0083517   .0484588    -0.17   0.863    -.1034284    .0867249
          imonthdum5 |   -.008503   .0483028    -0.18   0.860    -.1032736    .0862677
          imonthdum6 |  -.0433353   .0447937    -0.97   0.334     -.131221    .0445504
          imonthdum7 |  -.0310459   .0404105    -0.77   0.442    -.1103317    .0482399
          imonthdum8 |  -.0485411   .0512234    -0.95   0.344    -.1490418    .0519596
          imonthdum9 |   -.062225   .1022535    -0.61   0.543    -.2628473    .1383973
         imonthdum10 |   .0484584   .1028924     0.47   0.638    -.1534174    .2503343
         imonthdum11 |   .0001952   .0532124     0.00   0.997     -.104208    .1045984
         imonthdum12 |  -.0239828   .0411706    -0.58   0.560    -.1047599    .0567944
         imonthdum13 |  -.0637384   .0518287    -1.23   0.219    -.1654269    .0379501
         imonthdum14 |  -.0240557   .0448901    -0.54   0.592    -.1121304    .0640191
         imonthdum15 |   -.017997   .0526366    -0.34   0.732    -.1212705    .0852765
         imonthdum16 |   .0391231    .053165     0.74   0.462    -.0651872    .1434333
         imonthdum17 |   .0928831    .053251     1.74   0.081    -.0115958    .1973621
         imonthdum18 |   .1833462   .0708397     2.59   0.010     .0443581    .3223344
         imonthdum19 |   .1660126   .0614081     2.70   0.007     .0455294    .2864959
         imonthdum20 |   .1350733    .045321     2.98   0.003      .046153    .2239935
ZLNpc_new_cases_7day |  -.0277355   .3413222    -0.08   0.935    -.6974128    .6419418
       out_workforce |   .0006924   .0198689     0.03   0.972    -.0382905    .0396754
            employed |  -.0058448   .0177445    -0.33   0.742    -.0406598    .0289701
              income |   .0006404   .0020796     0.31   0.758    -.0034397    .0047206
Y3h6_facialcoverings |   .0026294   .0327885     0.08   0.936    -.0617019    .0669607
                male |   -.039815   .0079934    -4.98   0.000    -.0554981   -.0241319
               age10 |   .0115305   .0051515     2.24   0.025     .0014232    .0216378
          age_group4 |   .0027263    .016804     0.16   0.871    -.0302434     .035696
     live_w_children |  -.0129872   .0083731    -1.55   0.121    -.0294154    .0034409
             somecol |   .0281901   .0136494     2.07   0.039     .0014099    .0549703
                  ba |   .0592607   .0129718     4.57   0.000     .0338099    .0847116
                grad |   .0602775   .0114543     5.26   0.000      .037804     .082751
             AmerInd |  -.0060378   .0324788    -0.19   0.853    -.0697615     .057686
               Asian |   .0334791   .0217815     1.54   0.125    -.0092564    .0762146
               Black |    .022726   .0134588     1.69   0.092    -.0036802    .0491322
                Hisp |  -.0009009   .0098209    -0.09   0.927    -.0201695    .0183678
         Multiracial |   .0099916    .024008     0.42   0.677    -.0371123    .0570954
               _cons |   .6528872   .1196639     5.46   0.000     .4181055     .887669
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       240           1         239     |
      ctyfip |      1162        1162           0    *|
  cty_x_time |     21420          81       21339     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Mask", replace) ///
> title("Worn mask (base month April 2020)") xtitle("Pandemic Month")
(file Mask.gph not found)
file Mask.gph saved

. 
. 
. *Very Worried Ill
. 
. estimates clear

. reghdfe v_worry_ill dem indep_third dmonthdum4-dmonthdum20 imonthdum4-imonthdum20  $controls_fe_model Yc4_restrictionsongathe
> rings Yc6_stayathomerequirements [aw=WEIGHT]  if minmonthworry==4  , a(time pid) vce(cl ctyfip)
(dropped 3181 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     53,892
Absorbing 2 HDFE groups                           F(  42,   2030) =       4.34
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6417
                                                  Adj R-squared   =     0.4731
                                                  Within R-sq.    =     0.0125
Number of clusters (ctyfip)  =      2,031         Root MSE        =     0.2223

                                             (Std. err. adjusted for 2,031 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .0261601   .0173872     1.50   0.133    -.0079385    .0602587
                 indep_third |  -.0203861   .0116189    -1.75   0.079    -.0431724    .0024002
                  dmonthdum4 |  -.0283971   .0178538    -1.59   0.112    -.0634108    .0066166
                  dmonthdum5 |  -.0200062   .0156989    -1.27   0.203    -.0507937    .0107813
                  dmonthdum6 |   .0465667   .0189563     2.46   0.014     .0093909    .0837424
                  dmonthdum7 |   .0580364   .0177506     3.27   0.001     .0232251    .0928476
                  dmonthdum8 |   .0678837   .0379012     1.79   0.073    -.0064456     .142213
                  dmonthdum9 |   .1031961   .0317096     3.25   0.001     .0410094    .1653828
                 dmonthdum10 |   .0767488   .0448407     1.71   0.087    -.0111898    .1646874
                 dmonthdum11 |   .0210712   .0267197     0.79   0.430    -.0313296     .073472
                 dmonthdum12 |    .005604   .0221285     0.25   0.800    -.0377929    .0490008
                 dmonthdum13 |   .0133739   .0269336     0.50   0.620    -.0394463    .0661942
                 dmonthdum14 |  -.0533173   .0216914    -2.46   0.014     -.095857   -.0107776
                 dmonthdum15 |  -.0600368   .0231951    -2.59   0.010    -.1055254   -.0145481
                 dmonthdum16 |  -.1279133   .0230459    -5.55   0.000    -.1731094   -.0827172
                 dmonthdum17 |  -.0854412   .0192252    -4.44   0.000    -.1231443    -.047738
                 dmonthdum18 |  -.0873809   .0279529    -3.13   0.002    -.1422003   -.0325616
                 dmonthdum19 |  -.0644211   .0273729    -2.35   0.019    -.1181029   -.0107392
                 dmonthdum20 |  -.0712826   .0233387    -3.05   0.002    -.1170529   -.0255123
                  imonthdum4 |   .0224644   .0199186     1.13   0.260    -.0165987    .0615275
                  imonthdum5 |   .0360655   .0166119     2.17   0.030     .0034874    .0686436
                  imonthdum6 |   .0601537   .0192193     3.13   0.002      .022462    .0978454
                  imonthdum7 |   .0301986   .0185416     1.63   0.104    -.0061639    .0665611
                  imonthdum8 |   .0298561   .0330025     0.90   0.366    -.0348662    .0945783
                  imonthdum9 |   .0778971   .0367745     2.12   0.034     .0057774    .1500168
                 imonthdum10 |   .0171154   .0397536     0.43   0.667    -.0608467    .0950775
                 imonthdum11 |  -.0081065   .0243957    -0.33   0.740    -.0559497    .0397366
                 imonthdum12 |   .0340311   .0224501     1.52   0.130    -.0099966    .0780588
                 imonthdum13 |   .0359942   .0217529     1.65   0.098    -.0066662    .0786546
                 imonthdum14 |   .0012564   .0180617     0.07   0.945     -.034165    .0366779
                 imonthdum15 |   .0393241   .0228666     1.72   0.086    -.0055202    .0841685
                 imonthdum16 |   .0006341   .0229012     0.03   0.978    -.0442782    .0455464
                 imonthdum17 |  -.0009981    .021768    -0.05   0.963    -.0436881    .0416918
                 imonthdum18 |   .0151108   .0217974     0.69   0.488    -.0276367    .0578583
                 imonthdum19 |   .0070249   .0209804     0.33   0.738    -.0341205    .0481704
                 imonthdum20 |   .0076423   .0202477     0.38   0.706    -.0320662    .0473507
        ZLNpc_new_cases_7day |   .0102603    .003616     2.84   0.005     .0031689    .0173517
               out_workforce |  -.0358973   .0223295    -1.61   0.108    -.0796884    .0078939
                    employed |  -.0319495    .019935    -1.60   0.109    -.0710446    .0071456
                      income |  -.0016967   .0034355    -0.49   0.621    -.0084342    .0050408
Yc4_restrictionsongatherings |  -.0029942   .0110589    -0.27   0.787    -.0246822    .0186938
  Yc6_stayathomerequirements |   .0098692   .0076767     1.29   0.199    -.0051858    .0249242
                       _cons |   .1324299   .0258739     5.12   0.000     .0816877    .1831722
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       256           1         255     |
         pid |     16946       16946           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe v_worry_ill dem indep_third dmonthdum4-dmonthdum20 imonthdum4-imonthdum20 $controls_fe_model Yc4_restrictionsongather
> ings Yc6_stayathomerequirements $controls_main_model  [aw=WEIGHT], a(time ctyfip cty_x_time) vce(cl ctyfip)
(dropped 49371 singleton observations)
(MWFE estimator converged in 650 iterations)

HDFE Linear regression                            Number of obs   =     65,005
Absorbing 3 HDFE groups                           F(  54,   1141) =      10.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6060
                                                  Adj R-squared   =     0.4049
                                                  Within R-sq.    =     0.0337
Number of clusters (ctyfip)  =      1,142         Root MSE        =     0.2418

                                             (Std. err. adjusted for 1,142 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .1103739   .0212373     5.20   0.000     .0687054    .1520423
                 indep_third |   .0701954   .0237461     2.96   0.003     .0236045    .1167863
                  dmonthdum4 |   .0016161   .0294728     0.05   0.956    -.0562108     .059443
                  dmonthdum5 |   .0121662   .0347263     0.35   0.726    -.0559683    .0803008
                  dmonthdum6 |   .0784234   .0348092     2.25   0.024     .0101261    .1467206
                  dmonthdum7 |  -.0092092   .0415057    -0.22   0.824    -.0906453     .072227
                  dmonthdum8 |    .019276   .0580545     0.33   0.740    -.0946296    .1331815
                  dmonthdum9 |  -.0564684    .052143    -1.08   0.279    -.1587753    .0458384
                 dmonthdum10 |   .0171844   .0705584     0.24   0.808    -.1212544    .1556232
                 dmonthdum11 |   .0649436   .0402156     1.61   0.107    -.0139613    .1438485
                 dmonthdum12 |   .0240283   .0329169     0.73   0.466    -.0405561    .0886128
                 dmonthdum13 |   .0255072   .0366704     0.70   0.487    -.0464418    .0974563
                 dmonthdum14 |  -.0228969    .026609    -0.86   0.390    -.0751049    .0293111
                 dmonthdum15 |  -.0270141    .031086    -0.87   0.385    -.0880061     .033978
                 dmonthdum16 |   -.080659   .0275076    -2.93   0.003    -.1346301   -.0266879
                 dmonthdum17 |  -.0731877    .027769    -2.64   0.009    -.1276718   -.0187036
                 dmonthdum18 |  -.0651575   .0285414    -2.28   0.023     -.121157   -.0091581
                 dmonthdum19 |  -.0469138   .0257372    -1.82   0.069    -.0974114    .0035838
                 dmonthdum20 |  -.0206617   .0294336    -0.70   0.483    -.0784117    .0370883
                  imonthdum4 |  -.0192009   .0315519    -0.61   0.543     -.081107    .0427053
                  imonthdum5 |  -.0192332   .0328375    -0.59   0.558    -.0836619    .0451955
                  imonthdum6 |   .0709022   .0323116     2.19   0.028     .0075054     .134299
                  imonthdum7 |  -.0033213    .038843    -0.09   0.932    -.0795331    .0728905
                  imonthdum8 |  -.0207743   .0680794    -0.31   0.760    -.1543492    .1128006
                  imonthdum9 |  -.0373211   .0476901    -0.78   0.434    -.1308912     .056249
                 imonthdum10 |   .0074602   .0532673     0.14   0.889    -.0970527    .1119731
                 imonthdum11 |   .0297141    .046926     0.63   0.527    -.0623568     .121785
                 imonthdum12 |   .0098739    .032418     0.30   0.761    -.0537317    .0734795
                 imonthdum13 |  -.0405633   .0320635    -1.27   0.206    -.1034733    .0223467
                 imonthdum14 |   -.028126   .0295198    -0.95   0.341    -.0860452    .0297931
                 imonthdum15 |  -.0221069   .0342189    -0.65   0.518    -.0892459     .045032
                 imonthdum16 |  -.0703651   .0230255    -3.06   0.002    -.1155423    -.025188
                 imonthdum17 |  -.0427867   .0291706    -1.47   0.143    -.1000207    .0144474
                 imonthdum18 |  -.0235999   .0357219    -0.66   0.509    -.0936879    .0464881
                 imonthdum19 |  -.0450356    .029942    -1.50   0.133    -.1037831     .013712
                 imonthdum20 |  -.0212908   .0306785    -0.69   0.488    -.0814834    .0389017
        ZLNpc_new_cases_7day |  -.1109307   .1438413    -0.77   0.441    -.3931539    .1712925
               out_workforce |  -.0453777   .0186386    -2.43   0.015    -.0819475    -.008808
                    employed |  -.0387958   .0176672    -2.20   0.028    -.0734597    -.004132
                      income |  -.0031972    .001739    -1.84   0.066    -.0066091    .0002148
Yc4_restrictionsongatherings |  -.0944899   .0556748    -1.70   0.090    -.2037264    .0147467
  Yc6_stayathomerequirements |   -.003054   .0657106    -0.05   0.963    -.1319811    .1258731
                        male |  -.0337234   .0087339    -3.86   0.000    -.0508598    -.016587
                       age10 |  -.0040923   .0038895    -1.05   0.293    -.0117237    .0035391
                  age_group4 |  -.0108638   .0148839    -0.73   0.466    -.0400666    .0183391
             live_w_children |   .0066387    .007587     0.88   0.382    -.0082472    .0215247
                     somecol |   .0095556     .01196     0.80   0.424    -.0139105    .0330217
                          ba |  -.0012072   .0132438    -0.09   0.927     -.027192    .0247777
                        grad |    .003891   .0147785     0.26   0.792    -.0251051    .0328872
                     AmerInd |   .0279749   .0724431     0.39   0.699    -.1141618    .1701116
                       Asian |   .0337605   .0326464     1.03   0.301    -.0302933    .0978143
                       Black |   -.008085   .0156648    -0.52   0.606      -.03882    .0226499
                        Hisp |   .0220299   .0156272     1.41   0.159    -.0086314    .0526912
                 Multiracial |   .0509898   .0224314     2.27   0.023     .0069784    .0950012
                       _cons |   .2429896   .0743909     3.27   0.001     .0970312     .388948
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       236           1         235     |
      ctyfip |      1142        1142           0    *|
  cty_x_time |     20616          82       20534     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Worry", replace) ///
> title("Very worried about COVID (base month April 2020)") xtitle("Pandemic Month")
(file Worry.gph not found)
file Worry.gph saved

. 
. 
. *Mostly remote
. 
. estimates clear

. reghdfe mostly_remote dem indep_third  dmonthdum5-dmonthdum20 imonthdum5-imonthdum20  ZLNpc_new_cases_7day income Yc4_restric
> tionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing  [aw=WEIGHT]  if (minmonthmostly_remote==4 | minmonthmostly
> _remote==5)  &  employed==1, a(time pid) vce(cl ctyfip)
(dropped 2118 singleton observations)
(MWFE estimator converged in 13 iterations)

HDFE Linear regression                            Number of obs   =     21,566
Absorbing 2 HDFE groups                           F(  39,   1437) =       0.96
Statistics robust to heteroskedasticity           Prob > F        =     0.5344
                                                  R-squared       =     0.8038
                                                  Adj R-squared   =     0.7021
                                                  Within R-sq.    =     0.0042
Number of clusters (ctyfip)  =      1,438         Root MSE        =     0.2727

                                             (Std. err. adjusted for 1,438 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .0184195   .0320298     0.58   0.565    -.0444106    .0812496
                 indep_third |   .0106622   .0268304     0.40   0.691    -.0419689    .0632932
                  dmonthdum5 |  -.0030543   .0314081    -0.10   0.923    -.0646649    .0585562
                  dmonthdum6 |  -.0004066   .0303578    -0.01   0.989     -.059957    .0591438
                  dmonthdum7 |   .0282925   .0364515     0.78   0.438    -.0432113    .0997963
                  dmonthdum8 |  -.0609731   .0628971    -0.97   0.333    -.1843532     .062407
                  dmonthdum9 |  -.0621721   .0605946    -1.03   0.305    -.1810355    .0566913
                 dmonthdum10 |   .0607383   .0717028     0.85   0.397    -.0799151    .2013917
                 dmonthdum11 |  -.0661789   .0404746    -1.64   0.102    -.1455746    .0132168
                 dmonthdum12 |  -.0625459   .0432837    -1.45   0.149     -.147452    .0223602
                 dmonthdum13 |  -.0215312   .0360072    -0.60   0.550    -.0921635     .049101
                 dmonthdum14 |   .0280916   .0433099     0.65   0.517    -.0568657     .113049
                 dmonthdum15 |  -.0837657   .0498463    -1.68   0.093    -.1815449    .0140136
                 dmonthdum16 |  -.0251341   .0461934    -0.54   0.586    -.1157478    .0654795
                 dmonthdum17 |    .007426   .0473013     0.16   0.875     -.085361    .1002129
                 dmonthdum18 |  -.0219218   .0535035    -0.41   0.682    -.1268751    .0830314
                 dmonthdum19 |   .0127181   .0609067     0.21   0.835    -.1067575    .1321936
                 dmonthdum20 |  -.0998249    .049616    -2.01   0.044    -.1971525   -.0024973
                  imonthdum5 |  -.0205746   .0351384    -0.59   0.558    -.0895026    .0483535
                  imonthdum6 |  -.0232531   .0329381    -0.71   0.480    -.0878649    .0413588
                  imonthdum7 |  -.0152878   .0324837    -0.47   0.638    -.0790084    .0484327
                  imonthdum8 |  -.0970407   .0666458    -1.46   0.146    -.2277741    .0336927
                  imonthdum9 |  -.0948171   .0588496    -1.61   0.107    -.2102574    .0206232
                 imonthdum10 |   .0489443   .0634106     0.77   0.440     -.075443    .1733317
                 imonthdum11 |  -.0591954   .0433586    -1.37   0.172    -.1442483    .0258575
                 imonthdum12 |  -.0529729   .0482273    -1.10   0.272    -.1475763    .0416305
                 imonthdum13 |  -.0350456   .0427566    -0.82   0.413    -.1189176    .0488264
                 imonthdum14 |  -.0052603   .0437872    -0.12   0.904    -.0911539    .0806333
                 imonthdum15 |  -.0345441   .0571963    -0.60   0.546    -.1467413    .0776531
                 imonthdum16 |    .016441   .0545542     0.30   0.763    -.0905733    .1234554
                 imonthdum17 |   .0159918   .0458732     0.35   0.727    -.0739938    .1059774
                 imonthdum18 |   .0441107   .0535213     0.82   0.410    -.0608775    .1490989
                 imonthdum19 |   .0001563    .063733     0.00   0.998    -.1248634    .1251761
                 imonthdum20 |  -.1208385   .0509438    -2.37   0.018    -.2207706   -.0209064
        ZLNpc_new_cases_7day |  -.0040423   .0074665    -0.54   0.588    -.0186888    .0106042
                      income |   .0004872    .006874     0.07   0.944    -.0129969    .0139714
Yc4_restrictionsongatherings |  -.0178938   .0167502    -1.07   0.286    -.0507512    .0149637
  Yc6_stayathomerequirements |  -.0054589   .0126014    -0.43   0.665    -.0301779    .0192602
        Yc2_workplaceclosing |    .005757   .0120543     0.48   0.633    -.0178889    .0294029
                       _cons |   .4865893   .0515949     9.43   0.000     .3853799    .5877987
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       238           1         237     |
         pid |      7089        7089           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe mostly_remote dem indep_third  dmonthdum5-dmonthdum20 imonthdum5-imonthdum20 ZLNpc_new_cases_7day  income Yc4_restric
> tionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing  $controls_main_model  if  employed==1 [aw=WEIGHT], a(time 
> ctyfip cty_x_time) vce(cl ctyfip)
(dropped 29325 singleton observations)
(MWFE estimator converged in 55 iterations)
note: ZLNpc_new_cases_7day is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0
> e-09)

HDFE Linear regression                            Number of obs   =     22,850
Absorbing 3 HDFE groups                           F(  50,    680) =      19.73
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6569
                                                  Adj R-squared   =     0.4357
                                                  Within R-sq.    =     0.1275
Number of clusters (ctyfip)  =        681         Root MSE        =     0.3754

                                               (Std. err. adjusted for 681 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .1411747   .0588276     2.40   0.017     .0256692    .2566802
                 indep_third |   .0647303   .0567537     1.14   0.254    -.0467033     .176164
                  dmonthdum5 |   .0536669   .0956671     0.56   0.575    -.1341716    .2415053
                  dmonthdum6 |   .0276269    .069708     0.40   0.692    -.1092419    .1644957
                  dmonthdum7 |   .0105795   .0972133     0.11   0.913    -.1802947    .2014537
                  dmonthdum8 |   .1219336   .1375192     0.89   0.376    -.1480798    .3919469
                  dmonthdum9 |   .0700566   .1699927     0.41   0.680    -.2637171    .4038303
                 dmonthdum10 |   .0018632   .1392911     0.01   0.989     -.271629    .2753555
                 dmonthdum11 |   -.046545   .0975748    -0.48   0.634    -.2381292    .1450391
                 dmonthdum12 |  -.0219023   .1066397    -0.21   0.837    -.2312849    .1874804
                 dmonthdum13 |  -.0290629   .0860762    -0.34   0.736    -.1980699    .1399441
                 dmonthdum14 |   .0226978   .0899867     0.25   0.801    -.1539873    .1993828
                 dmonthdum15 |   .0090804   .0842425     0.11   0.914    -.1563263     .174487
                 dmonthdum16 |   .0955127   .0853577     1.12   0.264    -.0720836     .263109
                 dmonthdum17 |   .1420887   .0899183     1.58   0.115    -.0344622    .3186397
                 dmonthdum18 |   .0280688   .1184142     0.24   0.813    -.2044326    .2605702
                 dmonthdum19 |   .0543454   .1210907     0.45   0.654    -.1834113     .292102
                 dmonthdum20 |  -.0538533   .0896536    -0.60   0.548    -.2298844    .1221779
                  imonthdum5 |    .107054    .102039     1.05   0.294    -.0932954    .3074033
                  imonthdum6 |   .0151369   .0829695     0.18   0.855    -.1477703     .178044
                  imonthdum7 |   .0357369   .1021439     0.35   0.727    -.1648184    .2362921
                  imonthdum8 |   .2176037   .1449877     1.50   0.134    -.0670737    .5022811
                  imonthdum9 |  -.1433837   .1803474    -0.80   0.427    -.4974884    .2107209
                 imonthdum10 |   .1335213    .119098     1.12   0.263    -.1003227    .3673652
                 imonthdum11 |  -.1993033   .1038182    -1.92   0.055     -.403146    .0045394
                 imonthdum12 |   -.083847   .0991861    -0.85   0.398    -.2785948    .1109008
                 imonthdum13 |   .0131495    .097703     0.13   0.893    -.1786864    .2049853
                 imonthdum14 |  -.0293663   .0916135    -0.32   0.749    -.2092456    .1505131
                 imonthdum15 |   .0311684   .0850133     0.37   0.714    -.1357517    .1980886
                 imonthdum16 |    .015316   .0876905     0.17   0.861    -.1568607    .1874928
                 imonthdum17 |   .1198856   .0932155     1.29   0.199    -.0631393    .3029105
                 imonthdum18 |   .0317703   .1150876     0.28   0.783    -.1941995    .2577401
                 imonthdum19 |    .048753    .113544     0.43   0.668     -.174186     .271692
                 imonthdum20 |  -.0648628   .0833999    -0.78   0.437     -.228615    .0988895
        ZLNpc_new_cases_7day |          0  (omitted)
                      income |   .0411066   .0049273     8.34   0.000     .0314321     .050781
Yc4_restrictionsongatherings |  -.1095527   .1263843    -0.87   0.386     -.357703    .1385976
  Yc6_stayathomerequirements |  -.0681598    .082428    -0.83   0.409    -.2300038    .0936843
        Yc2_workplaceclosing |  -.0056807   .0868444    -0.07   0.948    -.1761962    .1648348
                        male |  -.0813055   .0181341    -4.48   0.000    -.1169111   -.0456999
                       age10 |  -.0257831   .0078967    -3.27   0.001     -.041288   -.0102783
                  age_group4 |   .0361464   .0320976     1.13   0.261    -.0268759    .0991687
             live_w_children |  -.0516164   .0176905    -2.92   0.004     -.086351   -.0168818
                     somecol |    .045431   .0267838     1.70   0.090    -.0071579    .0980199
                          ba |   .2177129   .0345226     6.31   0.000     .1499292    .2854966
                        grad |   .2043066   .0342789     5.96   0.000     .1370013    .2716118
                     AmerInd |   .0128021   .0894958     0.14   0.886    -.1629192    .1885234
                       Asian |   .1160142   .0643726     1.80   0.072    -.0103788    .2424071
                       Black |  -.0125116   .0311304    -0.40   0.688     -.073635    .0486117
                        Hisp |  -.0328702   .0429078    -0.77   0.444     -.117118    .0513775
                 Multiracial |   .0018846   .0491699     0.04   0.969    -.0946585    .0984277
                       _cons |   .2928802   .1026634     2.85   0.004     .0913049    .4944555
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       208           1         207     |
      ctyfip |       681         681           0    *|
  cty_x_time |      8177         159        8018     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Remote", replace) ///
> title("Mostly working remote (base month May 2020)") xtitle("Pandemic Month")
(file Remote.gph not found)
file Remote.gph saved

. 
. grc1leg MostlyIsolate.gph Mask.gph Worry.gph Remote.gph   ///
> , imargin(2 2 2 2) row(2) col(2) legendfrom(MostlyIsolate.gph) iscale(*.75) plotregion(color(white)) graphregion(color(white)
> )  

. graph export "figures\Figure S12.png", replace width(2200) height(1600)
file figures\Figure S12.png saved as PNG format

. 
. * Delete the intermediate files
. erase Remote.gph

. erase MostlyIsolate.gph

. erase Mask.gph

. erase Worry.gph

. 
. 
. ******************
. *** Figure S13 *** 
. ******************
. 
. *Change in Partisan Gap in COVID-19 Responses, States with Mask Mandates
. 
. clear

. use "data_gallup.dta"

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(4,143 real changes made)
(3,759 real changes made)
(3,905 real changes made)
(3,731 real changes made)
(3,572 real changes made)
(4,843 real changes made)
(3,475 real changes made)
(3,553 real changes made)
(4,034 real changes made)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(30,507 missing values generated)

. 
. *no individual fixed effects
. estimates clear

. reghdfe worn_mask dem indep_third   dmonthdum4-dmonthdum20  imonthdum4-imonthdum20  ZLNpc_new_cases_7day out_workforce employ
> ed live_w_children income  male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial [aw=WEIGHT]  if Y3h6_
> facialcoverings==1 , a(time ctyfip) vce(cl ctyfip)
(dropped 339 singleton observations)
(MWFE estimator converged in 9 iterations)

HDFE Linear regression                            Number of obs   =     58,066
Absorbing 2 HDFE groups                           F(  52,   1803) =      17.43
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2897
                                                  Adj R-squared   =     0.2627
                                                  Within R-sq.    =     0.0689
Number of clusters (ctyfip)  =      1,804         Root MSE        =     0.2811

                                     (Std. err. adjusted for 1,804 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |   .1597958      .0267     5.98   0.000     .1074296     .212162
         indep_third |   .1326302   .0279727     4.74   0.000     .0777679    .1874925
          dmonthdum4 |   .0006663   .0328402     0.02   0.984    -.0637427    .0650752
          dmonthdum5 |   .0248853   .0341009     0.73   0.466    -.0419961    .0917666
          dmonthdum6 |  -.0418654   .0296564    -1.41   0.158    -.1000299     .016299
          dmonthdum7 |  -.0673051   .0297832    -2.26   0.024    -.1257184   -.0088918
          dmonthdum8 |  -.1155765    .035499    -3.26   0.001    -.1852001   -.0459529
          dmonthdum9 |  -.0181401   .0392631    -0.46   0.644    -.0951461    .0588659
         dmonthdum10 |  -.0060957   .0379871    -0.16   0.873    -.0805991    .0684076
         dmonthdum11 |  -.0289991   .0335986    -0.86   0.388    -.0948955    .0368972
         dmonthdum12 |  -.0546649   .0318343    -1.72   0.086    -.1171009     .007771
         dmonthdum13 |  -.0205873   .0321766    -0.64   0.522    -.0836945      .04252
         dmonthdum14 |   .0009879   .0308082     0.03   0.974    -.0594356    .0614113
         dmonthdum15 |   .0259714   .0353108     0.74   0.462     -.043283    .0952258
         dmonthdum16 |    .114714   .0358281     3.20   0.001      .044445    .1849829
         dmonthdum17 |   .2634597   .0579337     4.55   0.000     .1498355     .377084
         dmonthdum18 |   .2804267   .0605135     4.63   0.000     .1617428    .3991105
         dmonthdum19 |    .332438   .0808531     4.11   0.000     .1738624    .4910136
         dmonthdum20 |   .1908378   .0787215     2.42   0.015      .036443    .3452327
          imonthdum4 |  -.0864202   .0385063    -2.24   0.025    -.1619418   -.0108987
          imonthdum5 |  -.0395857   .0392688    -1.01   0.314    -.1166028    .0374313
          imonthdum6 |  -.0840076   .0309119    -2.72   0.007    -.1446346   -.0233806
          imonthdum7 |  -.0611656   .0322279    -1.90   0.058    -.1243736    .0020425
          imonthdum8 |  -.1536734   .0427931    -3.59   0.000    -.2376026   -.0697441
          imonthdum9 |  -.0991514   .0512646    -1.93   0.053    -.1996956    .0013928
         imonthdum10 |  -.0586142   .0451575    -1.30   0.194    -.1471807    .0299523
         imonthdum11 |  -.0397964   .0359709    -1.11   0.269    -.1103454    .0307527
         imonthdum12 |  -.0822821   .0359787    -2.29   0.022    -.1528463   -.0117178
         imonthdum13 |  -.0826345   .0370083    -2.23   0.026    -.1552182   -.0100508
         imonthdum14 |   -.025616   .0338663    -0.76   0.450    -.0920374    .0408054
         imonthdum15 |  -.0470477   .0378419    -1.24   0.214    -.1212663     .027171
         imonthdum16 |  -.0501698    .046994    -1.07   0.286    -.1423381    .0419986
         imonthdum17 |    .078756   .0719621     1.09   0.274     -.062382    .2198939
         imonthdum18 |   .0815467   .0814924     1.00   0.317    -.0782827    .2413761
         imonthdum19 |  -.0283814   .0923366    -0.31   0.759    -.2094793    .1527166
         imonthdum20 |   .0694621   .0799562     0.87   0.385    -.0873544    .2262786
ZLNpc_new_cases_7day |   .0225364   .0050024     4.51   0.000     .0127253    .0323475
       out_workforce |  -.0043868    .012816    -0.34   0.732    -.0295225     .020749
            employed |  -.0086015   .0109195    -0.79   0.431    -.0300177    .0128146
     live_w_children |  -.0182982   .0069774    -2.62   0.009    -.0319829   -.0046136
              income |   .0004628   .0014122     0.33   0.743    -.0023069    .0032326
                male |  -.0396922   .0055249    -7.18   0.000    -.0505281   -.0288563
               age10 |   .0073363   .0033284     2.20   0.028     .0008084    .0138642
          age_group4 |   .0168425   .0111921     1.50   0.133    -.0051084    .0387934
             somecol |   .0275453    .008993     3.06   0.002     .0099076     .045183
                  ba |   .0643536   .0100889     6.38   0.000     .0445664    .0841407
                grad |     .06396   .0082553     7.75   0.000     .0477691    .0801509
             AmerInd |  -.0354987   .0509116    -0.70   0.486    -.1353507    .0643533
               Asian |   .0387567   .0145594     2.66   0.008     .0102016    .0673117
               Black |   .0031596   .0088601     0.36   0.721    -.0142176    .0205367
                Hisp |   .0011824   .0081414     0.15   0.885    -.0147852    .0171499
         Multiracial |  -.0017581   .0171573    -0.10   0.918    -.0354083    .0318921
               _cons |   .7398221   .0205611    35.98   0.000     .6994961    .7801481
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       268           1         267     |
      ctyfip |      1804        1804           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. *individual fixed effects
. reghdfe worn_mask dem indep_third   dmonthdum4-dmonthdum20  imonthdum4-imonthdum20  ZLNpc_new_cases_7day out_workforce employ
> ed income [aw=WEIGHT]  if minmonthmask==4 & Y3h6_facialcoverings==1 , a(time pid) vce(cl ctyfip)
(dropped 7254 singleton observations)
(MWFE estimator converged in 15 iterations)

HDFE Linear regression                            Number of obs   =     25,399
Absorbing 2 HDFE groups                           F(  40,   1259) =       3.46
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7001
                                                  Adj R-squared   =     0.5117
                                                  Within R-sq.    =     0.0221
Number of clusters (ctyfip)  =      1,260         Root MSE        =     0.2359

                                     (Std. err. adjusted for 1,260 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |  -.0334867    .041689    -0.80   0.422    -.1152743     .048301
         indep_third |    .001734   .0386095     0.04   0.964     -.074012    .0774801
          dmonthdum4 |   .0474126   .0515893     0.92   0.358    -.0537979     .148623
          dmonthdum5 |   .0463981   .0397589     1.17   0.243    -.0316029    .1243992
          dmonthdum6 |  -.0288608   .0350078    -0.82   0.410    -.0975409    .0398193
          dmonthdum7 |  -.0632752   .0340767    -1.86   0.064    -.1301285    .0035782
          dmonthdum8 |  -.0397636   .0465987    -0.85   0.394    -.1311833    .0516561
          dmonthdum9 |   .0665809   .0495759     1.34   0.180    -.0306796    .1638414
         dmonthdum10 |  -.0166551   .0415213    -0.40   0.688    -.0981136    .0648034
         dmonthdum11 |   .0000619   .0386327     0.00   0.999    -.0757297    .0758534
         dmonthdum12 |  -.0578029   .0379925    -1.52   0.128    -.1323384    .0167327
         dmonthdum13 |   .0017988   .0402943     0.04   0.964    -.0772527    .0808502
         dmonthdum14 |  -.0048433   .0406628    -0.12   0.905    -.0846177    .0749311
         dmonthdum15 |   .0328634   .0420763     0.78   0.435     -.049684    .1154109
         dmonthdum16 |   .1497509   .0541392     2.77   0.006     .0435379    .2559639
         dmonthdum17 |   .3012258   .0936903     3.22   0.001     .1174195    .4850321
         dmonthdum18 |   .3221005   .1015621     3.17   0.002     .1228509    .5213502
         dmonthdum19 |   .4057626    .154267     2.63   0.009     .1031139    .7084113
         dmonthdum20 |   .1298929   .1231267     1.05   0.292    -.1116632     .371449
          imonthdum4 |   .0141135   .0578517     0.24   0.807    -.0993829    .1276099
          imonthdum5 |  -.0246234   .0472859    -0.52   0.603    -.1173911    .0681444
          imonthdum6 |  -.0430632   .0376412    -1.14   0.253    -.1169095    .0307831
          imonthdum7 |   -.052511   .0390076    -1.35   0.178     -.129038     .024016
          imonthdum8 |  -.0527537   .0503373    -1.05   0.295    -.1515078    .0460005
          imonthdum9 |  -.0348324   .0579642    -0.60   0.548    -.1485495    .0788848
         imonthdum10 |  -.0211843   .0481164    -0.44   0.660    -.1155815    .0732129
         imonthdum11 |   .0402187   .0467063     0.86   0.389    -.0514121    .1318494
         imonthdum12 |  -.0768311   .0434627    -1.77   0.077    -.1620984    .0084362
         imonthdum13 |  -.0048234   .0460905    -0.10   0.917    -.0952461    .0855993
         imonthdum14 |  -.0302041   .0455024    -0.66   0.507     -.119473    .0590647
         imonthdum15 |  -.0030543    .048304    -0.06   0.950    -.0978196    .0917109
         imonthdum16 |  -.0038339    .061782    -0.06   0.951    -.1250409    .1173732
         imonthdum17 |  -.0233745   .1116288    -0.21   0.834    -.2423735    .1956245
         imonthdum18 |  -.0060215   .1276154    -0.05   0.962    -.2563837    .2443407
         imonthdum19 |    .250361   .1475133     1.70   0.090     -.039038    .5397601
         imonthdum20 |  -.1129625   .1549622    -0.73   0.466    -.4169751      .19105
ZLNpc_new_cases_7day |   .0197008    .007386     2.67   0.008     .0052106    .0341909
       out_workforce |  -.0002949   .0438828    -0.01   0.995    -.0863864    .0857965
            employed |   .0462459   .0350935     1.32   0.188    -.0226022    .1150941
              income |   .0011272   .0060747     0.19   0.853    -.0107903    .0130448
               _cons |   .8445952   .0445824    18.94   0.000     .7571312    .9320592
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       259           1         258     |
         pid |      9502        9502           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. quietly  coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) /
> //
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> legend(position(6) rows(1)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Mask_Mandate_Only", replace) ///
> title("Worn mask (base month April 2020)") xtitle("Pandemic Month")

. 
. graph export "figures\Figure S13.png", replace
file figures\Figure S13.png saved as PNG format

. 
. * Delete the intermediate files
. erase Mask_Mandate_Only.gph

. 
. 
. 
. ***************************
. *** Figures S14 and S15 *** 
. ***************************
. 
. *Month-party effects on COVID behaviors/attitudes for Democrats and Republicans, without individual fixed effects
. 
. clear

. use "data_gallup.dta"

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(4,143 real changes made)
(3,759 real changes made)
(3,905 real changes made)
(3,731 real changes made)
(3,572 real changes made)
(4,843 real changes made)
(3,475 real changes made)
(3,553 real changes made)
(4,034 real changes made)

. egen minmonthvac=min(month_number) if vaccinated!=., by(pid)
(264 missing values generated)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(30,507 missing values generated)

. egen minmonthisol=min(month_number) if Mostly_Isol!=., by(pid)
(5,890 missing values generated)

. egen minmonthworry=min(month_number) if v_worry_ill!=., by(pid)
(35,223 missing values generated)

. egen minmonthmostly_remote=min(month_number) if mostly_remote!=., by(pid)
(108,466 missing values generated)

. 
. 
. 
. **MODELS
. forvalues m=1/5 {
  2. foreach v in a b {
  3. foreach p in d g {
  4. forvalues i=2/20 {
  5. gen `p'coM`m'`v'`i'=.
  6. gen `p'seM`m'`v'`i'=.
  7. gen `p'ubM`m'`v'`i'=.
  8. gen `p'lbM`m'`v'`i'=.
  9. }
 10. }
 11. }
 12. }
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
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(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)
(164,327 missing values generated)

. 
. *Mostly Isolating
. 
. *M1-A-FixEff
. quietly reghdfe Mostly_Isol  dem gop dmonthdum3-dmonthdum20 gmonthdum3-gmonthdum20  ZLNpc_new_cases_7day out_workforce employ
> ed income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT]  if minmonthisol==3 ,  a(time pid) vce(cl ctyfi
> p)

. forval i = 3/20 {
  2. foreach p in d g {
  3. foreach t in a {
  4. foreach m in 1 {
  5. replace `p'coM`m'`t'`i'=_b[`p'monthdum`i'] 
  6. replace `p'seM`m'`t'`i'=_se[`p'monthdum`i'] 
  7. replace `p'ubM`m'`t'`i'=`p'coM`m'`t'`i'+1.96*`p'seM`m'`t'`i' 
  8. replace `p'lbM`m'`t'`i'=`p'coM`m'`t'`i'-1.96*`p'seM`m'`t'`i' 
  9. }
 10. }
 11. }
 12. }
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)

. 
. *M1-B-NO FixEff
. quietly reghdfe Mostly_Isol  dem gop dmonthdum3-dmonthdum20 gmonthdum3-gmonthdum20  ZLNpc_new_cases_7day out_workforce employ
> ed live_w_children income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT]   ,  a(time ctyfip) vce(cl ctyf
> ip)

. forval i = 3/20 {
  2. foreach p in d g {
  3. foreach t in b {
  4. foreach m in 1 {
  5. replace `p'coM`m'`t'`i'=_b[`p'monthdum`i'] 
  6. replace `p'seM`m'`t'`i'=_se[`p'monthdum`i'] 
  7. replace `p'ubM`m'`t'`i'=`p'coM`m'`t'`i'+1.96*`p'seM`m'`t'`i' 
  8. replace `p'lbM`m'`t'`i'=`p'coM`m'`t'`i'-1.96*`p'seM`m'`t'`i' 
  9. }
 10. }
 11. }
 12. }
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)

. 
. 
. *Very Worry Ill
. 
. *M2-A-FixEff
. quietly reghdfe v_worry_ill   dem gop dmonthdum4-dmonthdum20 gmonthdum4-gmonthdum20  ZLNpc_new_cases_7day out_workforce emplo
> yed income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT]  if minmonthworry==4 ,  a(time pid) vce(cl cty
> fip)

. forval i = 4/20 {
  2. foreach p in d g {
  3. foreach t in a {
  4. foreach m in 2 {
  5. replace `p'coM`m'`t'`i'=_b[`p'monthdum`i'] 
  6. replace `p'seM`m'`t'`i'=_se[`p'monthdum`i'] 
  7. replace `p'ubM`m'`t'`i'=`p'coM`m'`t'`i'+1.96*`p'seM`m'`t'`i' 
  8. replace `p'lbM`m'`t'`i'=`p'coM`m'`t'`i'-1.96*`p'seM`m'`t'`i' 
  9. }
 10. }
 11. }
 12. }
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)

. 
. *M2-B-NO FixEff
. quietly reghdfe v_worry_ill   dem gop dmonthdum4-dmonthdum20 gmonthdum4-gmonthdum20   ZLNpc_new_cases_7day out_workforce empl
> oyed live_w_children income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT]  if minmonthworry==4 ,  a(tim
> e ctyfip) vce(cl ctyfip)

. forval i = 4/20 {
  2. foreach p in d g {
  3. foreach t in b {
  4. foreach m in 2 {
  5. replace `p'coM`m'`t'`i'=_b[`p'monthdum`i'] 
  6. replace `p'seM`m'`t'`i'=_se[`p'monthdum`i'] 
  7. replace `p'ubM`m'`t'`i'=`p'coM`m'`t'`i'+1.96*`p'seM`m'`t'`i' 
  8. replace `p'lbM`m'`t'`i'=`p'coM`m'`t'`i'-1.96*`p'seM`m'`t'`i' 
  9. }
 10. }
 11. }
 12. }
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)

. 
. 
. *Mostly Remote
. 
. *M3-A-FixEff
. quietly reghdfe mostly_remote   dem gop dmonthdum5-dmonthdum20 gmonthdum5-gmonthdum20  ZLNpc_new_cases_7day out_workforce emp
> loyed income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT] if (minmonthmostly_remote==4 | minmonthmostl
> y_remote==5)  &  employed==1,  a(time pid) vce(cl ctyfip)

. forval i = 5/20 {
  2. foreach p in d g {
  3. foreach t in a {
  4. foreach m in 3 {
  5. replace `p'coM`m'`t'`i'=_b[`p'monthdum`i'] 
  6. replace `p'seM`m'`t'`i'=_se[`p'monthdum`i'] 
  7. replace `p'ubM`m'`t'`i'=`p'coM`m'`t'`i'+1.96*`p'seM`m'`t'`i' 
  8. replace `p'lbM`m'`t'`i'=`p'coM`m'`t'`i'-1.96*`p'seM`m'`t'`i' 
  9. }
 10. }
 11. }
 12. }
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)

. 
. *M3-B-NO FixEff
. quietly reghdfe mostly_remote  dem gop dmonthdum2 dmonthdum5-dmonthdum20 gmonthdum2 gmonthdum5-gmonthdum20   ZLNpc_new_cases_
> 7day out_workforce employed live_w_children income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT]  if  e
> mployed==1 ,  a(time ctyfip) vce(cl ctyfip)

. forval i = 5/20 {
  2. foreach p in d g {
  3. foreach t in b {
  4. foreach m in 3 {
  5. replace `p'coM`m'`t'`i'=_b[`p'monthdum`i'] 
  6. replace `p'seM`m'`t'`i'=_se[`p'monthdum`i'] 
  7. replace `p'ubM`m'`t'`i'=`p'coM`m'`t'`i'+1.96*`p'seM`m'`t'`i' 
  8. replace `p'lbM`m'`t'`i'=`p'coM`m'`t'`i'-1.96*`p'seM`m'`t'`i' 
  9. }
 10. }
 11. }
 12. }
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)

. 
. 
. *Worne Mask
. 
. *M4-A-FixEff
. quietly reghdfe worn_mask   dem gop dmonthdum2 dmonthdum4-dmonthdum20 gmonthdum2 gmonthdum4-gmonthdum20  ZLNpc_new_cases_7day
>  out_workforce employed income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT] if minmonthmask==4,  a(tim
> e pid) vce(cl ctyfip)

. forval i = 4/20 {
  2. foreach p in d g {
  3. foreach t in a {
  4. foreach m in 4 {
  5. replace `p'coM`m'`t'`i'=_b[`p'monthdum`i'] 
  6. replace `p'seM`m'`t'`i'=_se[`p'monthdum`i'] 
  7. replace `p'ubM`m'`t'`i'=`p'coM`m'`t'`i'+1.96*`p'seM`m'`t'`i' 
  8. replace `p'lbM`m'`t'`i'=`p'coM`m'`t'`i'-1.96*`p'seM`m'`t'`i' 
  9. }
 10. }
 11. }
 12. }
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)

. 
. *M4-B-NO FixEff
. quietly reghdfe worn_mask   dem gop dmonthdum2 dmonthdum4-dmonthdum20 gmonthdum2 gmonthdum4-gmonthdum20   ZLNpc_new_cases_7da
> y out_workforce employed live_w_children income Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT]  ,  a(tim
> e ctyfip) vce(cl ctyfip)

. forval i = 4/20 {
  2. foreach p in d g {
  3. foreach t in b {
  4. foreach m in 4 {
  5. replace `p'coM`m'`t'`i'=_b[`p'monthdum`i'] 
  6. replace `p'seM`m'`t'`i'=_se[`p'monthdum`i'] 
  7. replace `p'ubM`m'`t'`i'=`p'coM`m'`t'`i'+1.96*`p'seM`m'`t'`i' 
  8. replace `p'lbM`m'`t'`i'=`p'coM`m'`t'`i'-1.96*`p'seM`m'`t'`i' 
  9. }
 10. }
 11. }
 12. }
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
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(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)
(164,327 real changes made)

. 
. 
. collapse  dco* gco* dse* gse* dub* dlb*  gub* glb*

. 
. gen n=1

. reshape long dco gco dse gse gub glb dub dlb, i(n) j(type) string
(j = M1a10 M1a11 M1a12 M1a13 M1a14 M1a15 M1a16 M1a17 M1a18 M1a19 M1a2 M1a20 M1a3 M1a4 M1a5 M1a6 M1a7 M1a8 M1a9 M1b10 M1b11 M1b1
> 2 M1b13 M1b14 M1b15 M1b16 M1b17 M1b18 M1b19 M1b2 M1b20 M1b3 M1b4 M1b5 M1b6 M1b7 M1b8 M1b9 M2a10 M2a11 M2a12 M2a13 M2a14 M2a15
>  M2a16 M2a17 M2a18 M2a19 M2a2 M2a20 M2a3 M2a4 M2a5 M2a6 M2a7 M2a8 M2a9 M2b10 M2b11 M2b12 M2b13 M2b14 M2b15 M2b16 M2b17 M2b18 
> M2b19 M2b2 M2b20 M2b3 M2b4 M2b5 M2b6 M2b7 M2b8 M2b9 M3a10 M3a11 M3a12 M3a13 M3a14 M3a15 M3a16 M3a17 M3a18 M3a19 M3a2 M3a20 M3
> a3 M3a4 M3a5 M3a6 M3a7 M3a8 M3a9 M3b10 M3b11 M3b12 M3b13 M3b14 M3b15 M3b16 M3b17 M3b18 M3b19 M3b2 M3b20 M3b3 M3b4 M3b5 M3b6 M
> 3b7 M3b8 M3b9 M4a10 M4a11 M4a12 M4a13 M4a14 M4a15 M4a16 M4a17 M4a18 M4a19 M4a2 M4a20 M4a3 M4a4 M4a5 M4a6 M4a7 M4a8 M4a9 M4b10
>  M4b11 M4b12 M4b13 M4b14 M4b15 M4b16 M4b17 M4b18 M4b19 M4b2 M4b20 M4b3 M4b4 M4b5 M4b6 M4b7 M4b8 M4b9 M5a10 M5a11 M5a12 M5a13 
> M5a14 M5a15 M5a16 M5a17 M5a18 M5a19 M5a2 M5a20 M5a3 M5a4 M5a5 M5a6 M5a7 M5a8 M5a9 M5b10 M5b11 M5b12 M5b13 M5b14 M5b15 M5b16 M
> 5b17 M5b18 M5b19 M5b2 M5b20 M5b3 M5b4 M5b5 M5b6 M5b7 M5b8 M5b9)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                1   ->   190         
Number of variables               1,521   ->   10          
j variable (190 values)                   ->   type
xij variables:
          dcoM1a10 dcoM1a11 ... dcoM5b9   ->   dco
          gcoM1a10 gcoM1a11 ... gcoM5b9   ->   gco
          dseM1a10 dseM1a11 ... dseM5b9   ->   dse
          gseM1a10 gseM1a11 ... gseM5b9   ->   gse
          gubM1a10 gubM1a11 ... gubM5b9   ->   gub
          glbM1a10 glbM1a11 ... glbM5b9   ->   glb
          dubM1a10 dubM1a11 ... dubM5b9   ->   dub
          dlbM1a10 dlbM1a11 ... dlbM5b9   ->   dlb
-----------------------------------------------------------------------------

. tab type

       type |      Freq.     Percent        Cum.
------------+-----------------------------------
      M1a10 |          1        0.53        0.53
      M1a11 |          1        0.53        1.05
      M1a12 |          1        0.53        1.58
      M1a13 |          1        0.53        2.11
      M1a14 |          1        0.53        2.63
      M1a15 |          1        0.53        3.16
      M1a16 |          1        0.53        3.68
      M1a17 |          1        0.53        4.21
      M1a18 |          1        0.53        4.74
      M1a19 |          1        0.53        5.26
       M1a2 |          1        0.53        5.79
      M1a20 |          1        0.53        6.32
       M1a3 |          1        0.53        6.84
       M1a4 |          1        0.53        7.37
       M1a5 |          1        0.53        7.89
       M1a6 |          1        0.53        8.42
       M1a7 |          1        0.53        8.95
       M1a8 |          1        0.53        9.47
       M1a9 |          1        0.53       10.00
      M1b10 |          1        0.53       10.53
      M1b11 |          1        0.53       11.05
      M1b12 |          1        0.53       11.58
      M1b13 |          1        0.53       12.11
      M1b14 |          1        0.53       12.63
      M1b15 |          1        0.53       13.16
      M1b16 |          1        0.53       13.68
      M1b17 |          1        0.53       14.21
      M1b18 |          1        0.53       14.74
      M1b19 |          1        0.53       15.26
       M1b2 |          1        0.53       15.79
      M1b20 |          1        0.53       16.32
       M1b3 |          1        0.53       16.84
       M1b4 |          1        0.53       17.37
       M1b5 |          1        0.53       17.89
       M1b6 |          1        0.53       18.42
       M1b7 |          1        0.53       18.95
       M1b8 |          1        0.53       19.47
       M1b9 |          1        0.53       20.00
      M2a10 |          1        0.53       20.53
      M2a11 |          1        0.53       21.05
      M2a12 |          1        0.53       21.58
      M2a13 |          1        0.53       22.11
      M2a14 |          1        0.53       22.63
      M2a15 |          1        0.53       23.16
      M2a16 |          1        0.53       23.68
      M2a17 |          1        0.53       24.21
      M2a18 |          1        0.53       24.74
      M2a19 |          1        0.53       25.26
       M2a2 |          1        0.53       25.79
      M2a20 |          1        0.53       26.32
       M2a3 |          1        0.53       26.84
       M2a4 |          1        0.53       27.37
       M2a5 |          1        0.53       27.89
       M2a6 |          1        0.53       28.42
       M2a7 |          1        0.53       28.95
       M2a8 |          1        0.53       29.47
       M2a9 |          1        0.53       30.00
      M2b10 |          1        0.53       30.53
      M2b11 |          1        0.53       31.05
      M2b12 |          1        0.53       31.58
      M2b13 |          1        0.53       32.11
      M2b14 |          1        0.53       32.63
      M2b15 |          1        0.53       33.16
      M2b16 |          1        0.53       33.68
      M2b17 |          1        0.53       34.21
      M2b18 |          1        0.53       34.74
      M2b19 |          1        0.53       35.26
       M2b2 |          1        0.53       35.79
      M2b20 |          1        0.53       36.32
       M2b3 |          1        0.53       36.84
       M2b4 |          1        0.53       37.37
       M2b5 |          1        0.53       37.89
       M2b6 |          1        0.53       38.42
       M2b7 |          1        0.53       38.95
       M2b8 |          1        0.53       39.47
       M2b9 |          1        0.53       40.00
      M3a10 |          1        0.53       40.53
      M3a11 |          1        0.53       41.05
      M3a12 |          1        0.53       41.58
      M3a13 |          1        0.53       42.11
      M3a14 |          1        0.53       42.63
      M3a15 |          1        0.53       43.16
      M3a16 |          1        0.53       43.68
      M3a17 |          1        0.53       44.21
      M3a18 |          1        0.53       44.74
      M3a19 |          1        0.53       45.26
       M3a2 |          1        0.53       45.79
      M3a20 |          1        0.53       46.32
       M3a3 |          1        0.53       46.84
       M3a4 |          1        0.53       47.37
       M3a5 |          1        0.53       47.89
       M3a6 |          1        0.53       48.42
       M3a7 |          1        0.53       48.95
       M3a8 |          1        0.53       49.47
       M3a9 |          1        0.53       50.00
      M3b10 |          1        0.53       50.53
      M3b11 |          1        0.53       51.05
      M3b12 |          1        0.53       51.58
      M3b13 |          1        0.53       52.11
      M3b14 |          1        0.53       52.63
      M3b15 |          1        0.53       53.16
      M3b16 |          1        0.53       53.68
      M3b17 |          1        0.53       54.21
      M3b18 |          1        0.53       54.74
      M3b19 |          1        0.53       55.26
       M3b2 |          1        0.53       55.79
      M3b20 |          1        0.53       56.32
       M3b3 |          1        0.53       56.84
       M3b4 |          1        0.53       57.37
       M3b5 |          1        0.53       57.89
       M3b6 |          1        0.53       58.42
       M3b7 |          1        0.53       58.95
       M3b8 |          1        0.53       59.47
       M3b9 |          1        0.53       60.00
      M4a10 |          1        0.53       60.53
      M4a11 |          1        0.53       61.05
      M4a12 |          1        0.53       61.58
      M4a13 |          1        0.53       62.11
      M4a14 |          1        0.53       62.63
      M4a15 |          1        0.53       63.16
      M4a16 |          1        0.53       63.68
      M4a17 |          1        0.53       64.21
      M4a18 |          1        0.53       64.74
      M4a19 |          1        0.53       65.26
       M4a2 |          1        0.53       65.79
      M4a20 |          1        0.53       66.32
       M4a3 |          1        0.53       66.84
       M4a4 |          1        0.53       67.37
       M4a5 |          1        0.53       67.89
       M4a6 |          1        0.53       68.42
       M4a7 |          1        0.53       68.95
       M4a8 |          1        0.53       69.47
       M4a9 |          1        0.53       70.00
      M4b10 |          1        0.53       70.53
      M4b11 |          1        0.53       71.05
      M4b12 |          1        0.53       71.58
      M4b13 |          1        0.53       72.11
      M4b14 |          1        0.53       72.63
      M4b15 |          1        0.53       73.16
      M4b16 |          1        0.53       73.68
      M4b17 |          1        0.53       74.21
      M4b18 |          1        0.53       74.74
      M4b19 |          1        0.53       75.26
       M4b2 |          1        0.53       75.79
      M4b20 |          1        0.53       76.32
       M4b3 |          1        0.53       76.84
       M4b4 |          1        0.53       77.37
       M4b5 |          1        0.53       77.89
       M4b6 |          1        0.53       78.42
       M4b7 |          1        0.53       78.95
       M4b8 |          1        0.53       79.47
       M4b9 |          1        0.53       80.00
      M5a10 |          1        0.53       80.53
      M5a11 |          1        0.53       81.05
      M5a12 |          1        0.53       81.58
      M5a13 |          1        0.53       82.11
      M5a14 |          1        0.53       82.63
      M5a15 |          1        0.53       83.16
      M5a16 |          1        0.53       83.68
      M5a17 |          1        0.53       84.21
      M5a18 |          1        0.53       84.74
      M5a19 |          1        0.53       85.26
       M5a2 |          1        0.53       85.79
      M5a20 |          1        0.53       86.32
       M5a3 |          1        0.53       86.84
       M5a4 |          1        0.53       87.37
       M5a5 |          1        0.53       87.89
       M5a6 |          1        0.53       88.42
       M5a7 |          1        0.53       88.95
       M5a8 |          1        0.53       89.47
       M5a9 |          1        0.53       90.00
      M5b10 |          1        0.53       90.53
      M5b11 |          1        0.53       91.05
      M5b12 |          1        0.53       91.58
      M5b13 |          1        0.53       92.11
      M5b14 |          1        0.53       92.63
      M5b15 |          1        0.53       93.16
      M5b16 |          1        0.53       93.68
      M5b17 |          1        0.53       94.21
      M5b18 |          1        0.53       94.74
      M5b19 |          1        0.53       95.26
       M5b2 |          1        0.53       95.79
      M5b20 |          1        0.53       96.32
       M5b3 |          1        0.53       96.84
       M5b4 |          1        0.53       97.37
       M5b5 |          1        0.53       97.89
       M5b6 |          1        0.53       98.42
       M5b7 |          1        0.53       98.95
       M5b8 |          1        0.53       99.47
       M5b9 |          1        0.53      100.00
------------+-----------------------------------
      Total |        190      100.00

. gen mnum=substr(type,4,2)

. gen fig=substr(type,1,3)

. tab mnum

       mnum |      Freq.     Percent        Cum.
------------+-----------------------------------
         10 |         10        5.26        5.26
         11 |         10        5.26       10.53
         12 |         10        5.26       15.79
         13 |         10        5.26       21.05
         14 |         10        5.26       26.32
         15 |         10        5.26       31.58
         16 |         10        5.26       36.84
         17 |         10        5.26       42.11
         18 |         10        5.26       47.37
         19 |         10        5.26       52.63
          2 |         10        5.26       57.89
         20 |         10        5.26       63.16
          3 |         10        5.26       68.42
          4 |         10        5.26       73.68
          5 |         10        5.26       78.95
          6 |         10        5.26       84.21
          7 |         10        5.26       89.47
          8 |         10        5.26       94.74
          9 |         10        5.26      100.00
------------+-----------------------------------
      Total |        190      100.00

. tab fig

        fig |      Freq.     Percent        Cum.
------------+-----------------------------------
        M1a |         19       10.00       10.00
        M1b |         19       10.00       20.00
        M2a |         19       10.00       30.00
        M2b |         19       10.00       40.00
        M3a |         19       10.00       50.00
        M3b |         19       10.00       60.00
        M4a |         19       10.00       70.00
        M4b |         19       10.00       80.00
        M5a |         19       10.00       90.00
        M5b |         19       10.00      100.00
------------+-----------------------------------
      Total |        190      100.00

. destring mnum, replace
mnum: all characters numeric; replaced as byte

. 
. save "data\model_results_for_fig2_plots_dem_v_gop.dta", replace
file data\model_results_for_fig2_plots_dem_v_gop.dta saved

. use "data\model_results_for_fig2_plots_dem_v_gop.dta", clear

. 
. 
. *Mostly Isolating-FIX Ef A
. twoway rcap gub glb mnum if fig=="M1a", lcolor(red) lwidth(thin) lpattern(dash) || scatter gco mnum if fig=="M1a", mcolor(red
> ) msymbol(Oh)  ///
> || rcap dub dlb mnum if fig=="M1a", lcolor(blue) lwidth(thin) lpattern(solid) || scatter dco mnum if fig=="M1a", mcolor(blue)
>  msymbol(Dh) ///
> xlabel(3 "4/20"  4 " "  5 "6/20"  6 " "  7 "8/20"  8 " "  9 "10/20"  10 " "  11 "12/20" 12 " " 13 "2/22" 14 " " 15 "4/21" 16 
> " " 17 "6/21" 18 " " 19 "8/21" 20 " ") ///
> legend(pos(6) col(2)) ///
> legend(order (2 "Rep, 95% ci"  4 "Dem, 95% ci" ) ) ///
> plotregion(color(white)) graphregion(color(white))   ///
> yline(0, lc(black) lwidth(thin)) ///
> xline(13 14 15 , lwidth(.5in) lc(gray*.2)) ///
> xline(13 15, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> saving("MostlyIsolate_w_GOP_FE", replace) ///
> title("Mostly Isolating (base month March 2020)") xtitle("Pandemic Month")
(file MostlyIsolate_w_GOP_FE.gph not found)
file MostlyIsolate_w_GOP_FE.gph saved

. 
. *Mostly Isolating-B
. twoway rcap gub glb mnum if fig=="M1b", lcolor(red) lwidth(thin) lpattern(dash) || scatter gco mnum if fig=="M1b", mcolor(red
> ) msymbol(Oh)  ///
> || rcap dub dlb mnum if fig=="M1b", lcolor(blue) lwidth(thin) lpattern(solid) || scatter dco mnum if fig=="M1b", mcolor(blue)
>  msymbol(Dh) ///
> xlabel(3 "4/20"  4 " "  5 "6/20"  6 " "  7 "8/20"  8 " "  9 "10/20"  10 " "  11 "12/20" 12 " " 13 "2/22" 14 " " 15 "4/21" 16 
> " " 17 "6/21" 18 " " 19 "8/21" 20 " ") ///
> legend(pos(6) col(2)) ///
> legend(order (2 "Rep, 95% ci"  4 "Dem, 95% ci" ) ) ///
> plotregion(color(white)) graphregion(color(white))   ///
> yline(0, lc(black) lwidth(thin)) ///
> xline(13 14 15 , lwidth(.5in) lc(gray*.2)) ///
> xline(13 15, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> saving("MostlyIsolate_w_GOP", replace) ///
> title("Mostly Isolating (base month March 2020)") xtitle("Pandemic Month")
(file MostlyIsolate_w_GOP.gph not found)
file MostlyIsolate_w_GOP.gph saved

. 
. 
. *Very Worry Ill-FIX Ef A
. twoway rcap gub glb mnum if fig=="M2a", lcolor(red) lwidth(thin) lpattern(dash) || scatter gco mnum if fig=="M2a", mcolor(red
> ) msymbol(Oh)  ///
> || rcap dub dlb mnum if fig=="M2a", lcolor(blue) lwidth(thin) lpattern(solid) || scatter dco mnum if fig=="M2a", mcolor(blue)
>  msymbol(Dh) ///
> xlabel(3 "4/20"  4 " "  5 "6/20"  6 " "  7 "8/20"  8 " "  9 "10/20"  10 " "  11 "12/20" 12 " " 13 "2/22" 14 " " 15 "4/21" 16 
> " " 17 "6/21" 18 " " 19 "8/21" 20 " ") ///
> legend(pos(6) col(2)) ///
> legend(order (2 "Rep, 95% ci"  4 "Dem, 95% ci" ) ) ///
> plotregion(color(white)) graphregion(color(white))   ///
> yline(0, lc(black) lwidth(thin)) ///
> xline(13 14 15 , lwidth(.5in) lc(gray*.2)) ///
> xline(13 15, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> saving("Worry_w_GOP_FE", replace) ///
> title("Very worried about COVID (base month April 2020)") xtitle("Pandemic Month")
(file Worry_w_GOP_FE.gph not found)
file Worry_w_GOP_FE.gph saved

. 
. *Very Worry Ill-B
. twoway rcap gub glb mnum if fig=="M2b", lcolor(red) lwidth(thin) lpattern(dash) || scatter gco mnum if fig=="M2b", mcolor(red
> ) msymbol(Oh)  ///
> || rcap dub dlb mnum if fig=="M2b", lcolor(blue) lwidth(thin) lpattern(solid) || scatter dco mnum if fig=="M2b", mcolor(blue)
>  msymbol(Dh) ///
> xlabel(3 "4/20"  4 " "  5 "6/20"  6 " "  7 "8/20"  8 " "  9 "10/20"  10 " "  11 "12/20" 12 " " 13 "2/22" 14 " " 15 "4/21" 16 
> " " 17 "6/21" 18 " " 19 "8/21" 20 " ") ///
> legend(pos(6) col(2)) ///
> legend(order (2 "Rep, 95% ci"  4 "Dem, 95% ci" ) ) ///
> plotregion(color(white)) graphregion(color(white))   ///
> yline(0, lc(black) lwidth(thin)) ///
> xline(13 14 15 , lwidth(.5in) lc(gray*.2)) ///
> xline(13 15, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> saving("Worry_w_GOP", replace) ///
> title("Very worried about COVID (base month April 2020)") xtitle("Pandemic Month")
(file Worry_w_GOP.gph not found)
file Worry_w_GOP.gph saved

. 
. 
. *Mostly Remote-FIX Ef A
. twoway rcap gub glb mnum if fig=="M3a", lcolor(red) lwidth(thin) lpattern(dash) || scatter gco mnum if fig=="M3a", mcolor(red
> ) msymbol(Oh)  ///
> || rcap dub dlb mnum if fig=="M3a", lcolor(blue) lwidth(thin) lpattern(solid) || scatter dco mnum if fig=="M3a", mcolor(blue)
>  msymbol(Dh) ///
> xlabel(3 "4/20"  4 " "  5 "6/20"  6 " "  7 "8/20"  8 " "  9 "10/20"  10 " "  11 "12/20" 12 " " 13 "2/22" 14 " " 15 "4/21" 16 
> " " 17 "6/21" 18 " " 19 "8/21" 20 " ") ///
> legend(pos(6) col(2)) ///
> legend(order (2 "Rep, 95% ci"  4 "Dem, 95% ci" ) ) ///
> plotregion(color(white)) graphregion(color(white))   ///
> yline(0, lc(black) lwidth(thin)) ///
> xline(13 14 15 , lwidth(.5in) lc(gray*.2)) ///
> xline(13 15, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> saving("Remote_w_GOP_FE", replace) ///
> title("Mostly working remote (base month May 2020)") xtitle("Pandemic Month")
(file Remote_w_GOP_FE.gph not found)
file Remote_w_GOP_FE.gph saved

. 
. *Mostly Remote-B
. twoway rcap gub glb mnum if fig=="M3b", lcolor(red) lwidth(thin) lpattern(dash) || scatter gco mnum if fig=="M3b", mcolor(red
> ) msymbol(Oh)  ///
> || rcap dub dlb mnum if fig=="M3b", lcolor(blue) lwidth(thin) lpattern(solid) || scatter dco mnum if fig=="M3b", mcolor(blue)
>  msymbol(Dh) ///
> xlabel(3 "4/20"  4 " "  5 "6/20"  6 " "  7 "8/20"  8 " "  9 "10/20"  10 " "  11 "12/20" 12 " " 13 "2/22" 14 " " 15 "4/21" 16 
> " " 17 "6/21" 18 " " 19 "8/21" 20 " ") ///
> legend(pos(6) col(2)) ///
> legend(order (2 "Rep, 95% ci"  4 "Dem, 95% ci" ) ) ///
> plotregion(color(white)) graphregion(color(white))   ///
> yline(0, lc(black) lwidth(thin)) ///
> xline(13 14 15 , lwidth(.5in) lc(gray*.2)) ///
> xline(13 15, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> saving("Remote_w_GOP", replace) ///
> title("Mostly working remote (base month May 2020)") xtitle("Pandemic Month")
(file Remote_w_GOP.gph not found)
file Remote_w_GOP.gph saved

. 
. *Worn Mask-FIX Ef A
. twoway rcap gub glb mnum if fig=="M4a", lcolor(red) lwidth(thin) lpattern(dash) || scatter gco mnum if fig=="M4a", mcolor(red
> ) msymbol(Oh)  ///
> || rcap dub dlb mnum if fig=="M4a", lcolor(blue) lwidth(thin) lpattern(solid) || scatter dco mnum if fig=="M4a", mcolor(blue)
>  msymbol(Dh) ///
> xlabel(3 "4/20"  4 " "  5 "6/20"  6 " "  7 "8/20"  8 " "  9 "10/20"  10 " "  11 "12/20" 12 " " 13 "2/22" 14 " " 15 "4/21" 16 
> " " 17 "6/21" 18 " " 19 "8/21" 20 " ") ///
> legend(pos(6) col(2)) ///
> legend(order (2 "Rep, 95% ci"  4 "Dem, 95% ci" ) ) ///
> plotregion(color(white)) graphregion(color(white))   ///
> yline(0, lc(black) lwidth(thin)) ///
> xline(13 14 15 , lwidth(.5in) lc(gray*.2)) ///
> xline(13 15, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> saving("Mask_w_GOP_FE", replace) ///
> title("Worn mask (base month April 2020)") xtitle("Pandemic Month")
(file Mask_w_GOP_FE.gph not found)
file Mask_w_GOP_FE.gph saved

. 
. *Worn Mask-B
. twoway rcap gub glb mnum if fig=="M4b", lcolor(red) lwidth(thin) lpattern(dash) || scatter gco mnum if fig=="M4b", mcolor(red
> ) msymbol(Oh)  ///
> || rcap dub dlb mnum if fig=="M4b", lcolor(blue) lwidth(thin) lpattern(solid) || scatter dco mnum if fig=="M4b", mcolor(blue)
>  msymbol(Dh) ///
> xlabel(3 "4/20"  4 " "  5 "6/20"  6 " "  7 "8/20"  8 " "  9 "10/20"  10 " "  11 "12/20" 12 " " 13 "2/22" 14 " " 15 "4/21" 16 
> " " 17 "6/21" 18 " " 19 "8/21" 20 " ") ///
> legend(pos(6) col(2)) ///
> legend(order (2 "Rep, 95% ci"  4 "Dem, 95% ci" ) ) ///
> plotregion(color(white)) graphregion(color(white))   ///
> yline(0, lc(black) lwidth(thin)) ///
> xline(13 14 15 , lwidth(.5in) lc(gray*.2)) ///
> xline(13 15, lc(gray*.2) lpattern(dot) lwidth(thin)) ///
> saving("Mask_w_GOP", replace) ///
> title("Worn mask (base month April 2020)") xtitle("Pandemic Month")
(file Mask_w_GOP.gph not found)
file Mask_w_GOP.gph saved

. 
. grc1leg MostlyIsolate_w_GOP.gph Mask_w_GOP.gph Worry_w_GOP.gph Remote_w_GOP.gph   ///
> , imargin(2 2 2 2) row(2) col(2) legendfrom(MostlyIsolate_w_GOP.gph) iscale(*.75) plotregion(color(white)) graphregion(color(
> white))  

. graph export "figures\Figure S14.png", replace width(2200) height(1600)
file figures\Figure S14.png saved as PNG format

. 
. grc1leg MostlyIsolate_w_GOP_FE.gph Mask_w_GOP_FE.gph Worry_w_GOP_FE.gph Remote_w_GOP_FE.gph   ///
> , imargin(2 2 2 2) row(2) col(2) legendfrom(MostlyIsolate_w_GOP_FE.gph) iscale(*.75) plotregion(color(white)) graphregion(col
> or(white))  

. graph export "figures\Figure S15.png", replace width(2200) height(1600)
file figures\Figure S15.png saved as PNG format

. 
. * Delete the intermediate files
. erase MostlyIsolate_w_GOP.gph 

. erase Mask_w_GOP.gph 

. erase Worry_w_GOP.gph 

. erase Remote_w_GOP.gph

. erase MostlyIsolate_w_GOP_FE.gph 

. erase Mask_w_GOP_FE.gph 

. erase Worry_w_GOP_FE.gph 

. erase Remote_w_GOP_FE.gph

. 
. 
. ******************
. *** Figure S16 ***
. ******************
. 
. *Change in Effect of Income on Masking
. 
. clear

. use "data_gallup.dta"

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(4,143 real changes made)
(3,759 real changes made)
(3,905 real changes made)
(3,731 real changes made)
(3,572 real changes made)
(4,843 real changes made)
(3,475 real changes made)
(3,553 real changes made)
(4,034 real changes made)

. egen minmonthvac=min(month_number) if vaccinated!=., by(pid)
(264 missing values generated)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(30,507 missing values generated)

. egen minmonthisol=min(month_number) if Mostly_Isol!=., by(pid)
(5,890 missing values generated)

. egen minmonthworry=min(month_number) if v_worry_ill!=., by(pid)
(35,223 missing values generated)

. egen minmonthmostly_remote=min(month_number) if mostly_remote!=., by(pid)
(108,466 missing values generated)

. 
. tab month_num, gen(monthdum)

month_numbe |
          r |      Freq.     Percent        Cum.
------------+-----------------------------------
          3 |     22,801       13.88       13.88
          4 |     33,564       20.43       34.30
          5 |     17,757       10.81       45.11
          6 |     15,787        9.61       54.71
          7 |     16,375        9.96       64.68
          8 |     11,284        6.87       71.55
          9 |      2,730        1.66       73.21
         10 |      2,973        1.81       75.02
         11 |      2,982        1.81       76.83
         12 |      3,059        1.86       78.69
         13 |      4,143        2.52       81.21
         14 |      3,759        2.29       83.50
         15 |      3,905        2.38       85.88
         16 |      3,731        2.27       88.15
         17 |      3,572        2.17       90.32
         18 |      4,843        2.95       93.27
         19 |      3,475        2.11       95.38
         20 |      3,553        2.16       97.55
         21 |      4,034        2.45      100.00
------------+-----------------------------------
      Total |    164,327      100.00

. 
. forval i=1/19 {
  2. gen incomemonthdum`i'=income*monthdum`i'
  3. }
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)
(7,743 missing values generated)

. 
. *no individual fixed effects
. reghdfe worn_mask dem indep_third incomemonthdum3-incomemonthdum18 dmonthdum4-dmonthdum20  imonthdum4-imonthdum20  ZLNpc_new_
> cases_7day out_workforce employed live_w_children income  Y3h6_facialcoverings male age10 age_group4   somecol ba grad AmerIn
> d Asian Black Hisp Multiracial [aw=WEIGHT] , a(time ctyfip) vce(cl ctyfip)
(dropped 121 singleton observations)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =    118,436
Absorbing 2 HDFE groups                           F(  69,   2500) =      30.23
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3045
                                                  Adj R-squared   =     0.2875
                                                  Within R-sq.    =     0.0803
Number of clusters (ctyfip)  =      2,501         Root MSE        =     0.3348

                                     (Std. err. adjusted for 2,501 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |   .1691416   .0144192    11.73   0.000     .1408668    .1974163
         indep_third |   .0827379   .0160159     5.17   0.000     .0513322    .1141436
     incomemonthdum3 |    .002216   .0035148     0.63   0.528    -.0046763    .0091082
     incomemonthdum4 |   .0006861    .003194     0.21   0.830     -.005577    .0069492
     incomemonthdum5 |   .0019921   .0030413     0.66   0.513    -.0039716    .0079558
     incomemonthdum6 |  -.0002079    .003298    -0.06   0.950    -.0066751    .0062592
     incomemonthdum7 |   .0040349   .0061152     0.66   0.509    -.0079565    .0160263
     incomemonthdum8 |   .0037657   .0060601     0.62   0.534    -.0081177    .0156491
     incomemonthdum9 |   .0000967   .0052825     0.02   0.985    -.0102619    .0104553
    incomemonthdum10 |   .0012206   .0041445     0.29   0.768    -.0069065    .0093477
    incomemonthdum11 |   -.004156   .0032589    -1.28   0.202    -.0105464    .0022343
    incomemonthdum12 |  -.0043135   .0038609    -1.12   0.264    -.0118844    .0032575
    incomemonthdum13 |  -.0073135   .0033655    -2.17   0.030     -.013913   -.0007141
    incomemonthdum14 |  -.0062286   .0040521    -1.54   0.124    -.0141745    .0017173
    incomemonthdum15 |  -.0073386   .0039863    -1.84   0.066    -.0151554    .0004783
    incomemonthdum16 |  -.0125518   .0043175    -2.91   0.004    -.0210181   -.0040855
    incomemonthdum17 |  -.0166336   .0053581    -3.10   0.002    -.0271405   -.0061268
    incomemonthdum18 |  -.0125029   .0049556    -2.52   0.012    -.0222204   -.0027855
          dmonthdum4 |   .0358861   .0187599     1.91   0.056    -.0009003    .0726726
          dmonthdum5 |   .0588985   .0194873     3.02   0.003     .0206855    .0971114
          dmonthdum6 |  -.0306945   .0185748    -1.65   0.099     -.067118    .0057291
          dmonthdum7 |  -.0781389   .0191214    -4.09   0.000    -.1156344   -.0406435
          dmonthdum8 |  -.1059632   .0277384    -3.82   0.000    -.1603559   -.0515705
          dmonthdum9 |  -.0065427    .032584    -0.20   0.841    -.0704372    .0573517
         dmonthdum10 |   -.026682   .0282168    -0.95   0.344    -.0820127    .0286487
         dmonthdum11 |  -.0469416    .022514    -2.08   0.037    -.0910896   -.0027935
         dmonthdum12 |   -.071666   .0213336    -3.36   0.001    -.1134993   -.0298328
         dmonthdum13 |  -.0313384   .0226489    -1.38   0.167    -.0757509    .0130741
         dmonthdum14 |  -.0219365   .0201749    -1.09   0.277    -.0614977    .0176247
         dmonthdum15 |   .0154072   .0249697     0.62   0.537    -.0335563    .0643707
         dmonthdum16 |    .116074   .0247771     4.68   0.000     .0674883    .1646597
         dmonthdum17 |   .2030123   .0226007     8.98   0.000     .1586942    .2473304
         dmonthdum18 |   .2244388   .0300794     7.46   0.000     .1654556    .2834219
         dmonthdum19 |   .2701267   .0274356     9.85   0.000     .2163279    .3239255
         dmonthdum20 |   .2338474   .0240266     9.73   0.000     .1867333    .2809614
          imonthdum4 |   .0160893    .024092     0.67   0.504    -.0311531    .0633317
          imonthdum5 |   .0236307   .0231802     1.02   0.308    -.0218237     .069085
          imonthdum6 |  -.0023165   .0215559    -0.11   0.914    -.0445857    .0399527
          imonthdum7 |  -.0117611   .0222907    -0.53   0.598    -.0554713    .0319491
          imonthdum8 |  -.1008029   .0379727    -2.65   0.008    -.1752642   -.0263417
          imonthdum9 |  -.0195547   .0439692    -0.44   0.657    -.1057745    .0666651
         imonthdum10 |  -.0092556   .0363925    -0.25   0.799    -.0806182    .0621069
         imonthdum11 |   .0007224   .0262984     0.03   0.978    -.0508465    .0522914
         imonthdum12 |  -.0283094   .0252044    -1.12   0.261     -.077733    .0211141
         imonthdum13 |  -.0353021   .0273165    -1.29   0.196    -.0888673    .0182631
         imonthdum14 |   .0186596   .0240583     0.78   0.438    -.0285167    .0658359
         imonthdum15 |  -.0039939   .0280337    -0.14   0.887    -.0589657    .0509778
         imonthdum16 |   .0503359   .0312842     1.61   0.108    -.0110098    .1116815
         imonthdum17 |   .1058256   .0292672     3.62   0.000     .0484351    .1632161
         imonthdum18 |   .0942078   .0345426     2.73   0.006     .0264728    .1619428
         imonthdum19 |   .1006517   .0326098     3.09   0.002     .0367068    .1645967
         imonthdum20 |   .1133755   .0287155     3.95   0.000     .0570668    .1696842
ZLNpc_new_cases_7day |   .0314275    .003689     8.52   0.000     .0241937    .0386613
       out_workforce |  -.0003446   .0117676    -0.03   0.977    -.0234199    .0227307
            employed |  -.0088613   .0100254    -0.88   0.377    -.0285203    .0107977
     live_w_children |  -.0214377   .0060067    -3.57   0.000    -.0332163   -.0096591
              income |   .0002369    .002556     0.09   0.926    -.0047752     .005249
Y3h6_facialcoverings |   .0160785   .0065778     2.44   0.015     .0031801    .0289769
                male |  -.0488781   .0048466   -10.09   0.000    -.0583818   -.0393744
               age10 |   .0106903   .0028609     3.74   0.000     .0050803    .0163002
          age_group4 |   .0180892   .0097951     1.85   0.065    -.0011181    .0372966
             somecol |   .0336809   .0074558     4.52   0.000     .0190607     .048301
                  ba |   .0665529   .0078607     8.47   0.000     .0511387    .0819671
                grad |    .074401   .0073158    10.17   0.000     .0600553    .0887468
             AmerInd |   .0149919   .0432434     0.35   0.729    -.0698046    .0997885
               Asian |   .0360747   .0171749     2.10   0.036     .0023962    .0697531
               Black |   .0165693   .0081504     2.03   0.042      .000587    .0325516
                Hisp |   .0059159   .0071064     0.83   0.405    -.0080191     .019851
         Multiracial |  -.0169294   .0169391    -1.00   0.318    -.0501454    .0162867
               _cons |   .6285509    .017984    34.95   0.000     .5932859    .6638159
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       269           1         268     |
      ctyfip |      2501        2501           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. *individual fixed effects
. reghdfe worn_mask dem indep_third incomemonthdum3-incomemonthdum18 dmonthdum4-dmonthdum20  imonthdum4-imonthdum20  ZLNpc_new_
> cases_7day out_workforce employed income  Y3h6_facialcoverings [aw=WEIGHT]  if minmonthmask==4 , a(time pid) vce(cl ctyfip)
(dropped 3832 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     65,975
Absorbing 2 HDFE groups                           F(  57,   2149) =       6.85
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6226
                                                  Adj R-squared   =     0.4466
                                                  Within R-sq.    =     0.0222
Number of clusters (ctyfip)  =      2,150         Root MSE        =     0.3039

                                     (Std. err. adjusted for 2,150 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |  -.0715261   .0267665    -2.67   0.008     -.124017   -.0190351
         indep_third |  -.0753492   .0250931    -3.00   0.003    -.1245585   -.0261399
     incomemonthdum3 |  -.0010496   .0050886    -0.21   0.837    -.0110288    .0089295
     incomemonthdum4 |  -.0031449   .0039361    -0.80   0.424    -.0108639     .004574
     incomemonthdum5 |   .0017197   .0041597     0.41   0.679    -.0064378    .0098773
     incomemonthdum6 |  -.0073835   .0046062    -1.60   0.109    -.0164165    .0016495
     incomemonthdum7 |   .0115718   .0074663     1.55   0.121    -.0030701    .0262137
     incomemonthdum8 |   .0061772    .006943     0.89   0.374    -.0074385    .0197928
     incomemonthdum9 |   .0030032   .0074514     0.40   0.687    -.0116095    .0176158
    incomemonthdum10 |  -.0058028   .0057703    -1.01   0.315    -.0171186    .0055131
    incomemonthdum11 |  -.0041149    .004547    -0.90   0.366    -.0130318    .0048021
    incomemonthdum12 |   .0022351   .0050954     0.44   0.661    -.0077572    .0122275
    incomemonthdum13 |  -.0045911   .0059874    -0.77   0.443    -.0163328    .0071506
    incomemonthdum14 |  -.0061577   .0053089    -1.16   0.246    -.0165688    .0042533
    incomemonthdum15 |   -.003427   .0067819    -0.51   0.613    -.0167268    .0098728
    incomemonthdum16 |  -.0043336    .005957    -0.73   0.467    -.0160157    .0073484
    incomemonthdum17 |  -.0155888   .0079039    -1.97   0.049    -.0310888   -.0000887
    incomemonthdum18 |  -.0142315   .0078358    -1.82   0.069     -.029598    .0011351
          dmonthdum4 |   .0591904   .0275375     2.15   0.032     .0051876    .1131933
          dmonthdum5 |   .0869902   .0244974     3.55   0.000     .0389492    .1350313
          dmonthdum6 |  -.0148319    .022572    -0.66   0.511    -.0590971    .0294333
          dmonthdum7 |  -.0541887   .0239207    -2.27   0.024    -.1010988   -.0072787
          dmonthdum8 |  -.0752398   .0404847    -1.86   0.063     -.154633    .0041534
          dmonthdum9 |  -.0082634   .0422255    -0.20   0.845    -.0910706    .0745437
         dmonthdum10 |  -.0278532   .0322742    -0.86   0.388     -.091145    .0354387
         dmonthdum11 |   .0146464   .0286012     0.51   0.609    -.0414426    .0707354
         dmonthdum12 |  -.0740023   .0277977    -2.66   0.008    -.1285155   -.0194892
         dmonthdum13 |  -.0113452   .0316624    -0.36   0.720    -.0734373    .0507469
         dmonthdum14 |  -.0217287   .0291156    -0.75   0.456    -.0788265     .035369
         dmonthdum15 |   .0202155   .0332962     0.61   0.544    -.0450805    .0855116
         dmonthdum16 |    .127412   .0360597     3.53   0.000     .0566964    .1981276
         dmonthdum17 |    .210177   .0335194     6.27   0.000     .1444431    .2759109
         dmonthdum18 |    .218747   .0448722     4.87   0.000     .1307495    .3067445
         dmonthdum19 |    .250622   .0386449     6.49   0.000     .1748367    .3264072
         dmonthdum20 |   .2298817   .0321526     7.15   0.000     .1668282    .2929351
          imonthdum4 |   .0659418   .0320071     2.06   0.039     .0031736      .12871
          imonthdum5 |   .0491542   .0265359     1.85   0.064    -.0028844    .1011929
          imonthdum6 |   .0290659   .0259775     1.12   0.263    -.0218776    .0800095
          imonthdum7 |  -.0189247   .0278417    -0.68   0.497    -.0735243    .0356749
          imonthdum8 |  -.0923347    .045152    -2.04   0.041    -.1808809   -.0037886
          imonthdum9 |  -.0242822   .0526696    -0.46   0.645    -.1275709    .0790065
         imonthdum10 |   .0426308   .0414564     1.03   0.304    -.0386679    .1239295
         imonthdum11 |   .0974516   .0367944     2.65   0.008     .0252953    .1696079
         imonthdum12 |  -.0199552    .030244    -0.66   0.509    -.0792657    .0393552
         imonthdum13 |   .0308973   .0370416     0.83   0.404    -.0417438    .1035383
         imonthdum14 |   .0135296   .0332458     0.41   0.684    -.0516677    .0787269
         imonthdum15 |   .0456349   .0384337     1.19   0.235    -.0297361     .121006
         imonthdum16 |   .0908563   .0418764     2.17   0.030     .0087338    .1729788
         imonthdum17 |    .067308   .0418612     1.61   0.108    -.0147848    .1494007
         imonthdum18 |   .1148841   .0508845     2.26   0.024     .0150961    .2146721
         imonthdum19 |   .1332258   .0460086     2.90   0.004     .0429998    .2234519
         imonthdum20 |   .0897778   .0379104     2.37   0.018     .0154328    .1641227
ZLNpc_new_cases_7day |   .0357205    .005148     6.94   0.000     .0256248    .0458161
       out_workforce |   .0030227   .0270947     0.11   0.911    -.0501119    .0561573
            employed |   .0179815   .0238058     0.76   0.450    -.0287033    .0646663
              income |  -.0026668   .0049049    -0.54   0.587    -.0122857    .0069521
Y3h6_facialcoverings |   .0181492   .0092311     1.97   0.049     .0000463    .0362521
               _cons |   .8188601   .0368532    22.22   0.000     .7465885    .8911317
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       268           1         267     |
         pid |     20664       20664           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. quietly  coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) /
> //
> keep(incomemonthdum3 incomemonthdum4 incomemonthdum5 incomemonthdum6 incomemonthdum7 incomemonthdum8 incomemonthdum9 incomemo
> nthdum10 incomemonthdum11 incomemonthdum12 incomemonthdum13 incomemonthdum14 incomemonthdum15 incomemonthdum16 incomemonthdum
> 17 incomemonthdum18) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(incomemonthdum3 incomemonthdum4 incomemonthdum5 incomemonthdum6 incomemonthdum7 incomemonthdum8 incomemonthdum9 incomemo
> nthdum10 incomemonthdum11 incomemonthdum12 incomemonthdum13 incomemonthdum14 incomemonthdum15 incomemonthdum16 incomemonthdum
> 17 incomemonthdum18)), vertical ///
> coeflabels (incomemonthdum2="4/20" incomemonthdum3="5/20" incomemonthdum4="6/20" incomemonthdum5="7/20" incomemonthdum6="8/20
> " incomemonthdum7="9/20" incomemonthdum8="10/20" incomemonthdum9="11/20" incomemonthdum10="12/20" incomemonthdum11="1/21" inc
> omemonthdum12="2/21" incomemonthdum13="3/21" incomemonthdum14="4/21" incomemonthdum15="5/21" incomemonthdum16="6/21" incomemo
> nthdum17="7/21" incomemonthdum18="8/21" incomemonthdum19="9/21" )  xlabel(, angle(45)) ///
> legend(position(6) rows(1)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Mask_Income_Interaction.gph", replace) ///
> title("Worn mask (base month April 2020)") xtitle("Pandemic Month")

. 
. graph export "figures\Figure S16.png", replace
file figures\Figure S16.png saved as PNG format

. 
. * Delete the intermediate files
. erase Mask_Income_Interaction.gph

. 
. 
. ******************
. *** Figure S17 ***
. ******************
. 
. *Change in Partisan Gap in COVID-19 Responses, Controlling for Vaccination Status
. 
. clear

. use "data_gallup.dta"

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(4,143 real changes made)
(3,759 real changes made)
(3,905 real changes made)
(3,731 real changes made)
(3,572 real changes made)
(4,843 real changes made)
(3,475 real changes made)
(3,553 real changes made)
(4,034 real changes made)

. egen minmonthvac=min(month_number) if vaccinated!=., by(pid)
(264 missing values generated)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(30,507 missing values generated)

. egen minmonthisol=min(month_number) if Mostly_Isol!=., by(pid)
(5,890 missing values generated)

. egen minmonthworry=min(month_number) if v_worry_ill!=., by(pid)
(35,223 missing values generated)

. egen minmonthmostly_remote=min(month_number) if mostly_remote!=., by(pid)
(108,466 missing values generated)

. 
. *Mostly Isolate
. 
. estimates clear

. reghdfe Mostly_Isol vaccinated  dem indep_third dmonthdum3-dmonthdum20 imonthdum3-imonthdum20  Yc4_restrictionsongatherings Y
> c6_stayathomerequirements $controls_fe_model [aw=WEIGHT]  if minmonthisol==3 ,  a(time pid) vce(cl ctyfip)
(dropped 1673 singleton observations)
(MWFE estimator converged in 11 iterations)

HDFE Linear regression                            Number of obs   =     54,973
Absorbing 2 HDFE groups                           F(  45,   1939) =       5.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5869
                                                  Adj R-squared   =     0.4323
                                                  Within R-sq.    =     0.0162
Number of clusters (ctyfip)  =      1,940         Root MSE        =     0.3765

                                             (Std. err. adjusted for 1,940 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  vaccinated |  -.0803777    .016496    -4.87   0.000    -.1127296   -.0480259
                         dem |  -.1634918   .0322986    -5.06   0.000    -.2268354   -.1001482
                 indep_third |  -.1378359   .0272132    -5.07   0.000    -.1912061   -.0844657
                  dmonthdum3 |   .1011548   .0268366     3.77   0.000     .0485232    .1537864
                  dmonthdum4 |   .1704114   .0343994     4.95   0.000     .1029477     .237875
                  dmonthdum5 |   .1720942   .0327317     5.26   0.000     .1079012    .2362873
                  dmonthdum6 |   .1751144   .0347075     5.05   0.000     .1070465    .2431823
                  dmonthdum7 |   .2304672   .0405772     5.68   0.000     .1508877    .3100468
                  dmonthdum8 |   .1908576   .0758229     2.52   0.012     .0421547    .3395606
                  dmonthdum9 |   .2357775    .065492     3.60   0.000     .1073354    .3642196
                 dmonthdum10 |   .1448873   .0805201     1.80   0.072    -.0130278    .3028023
                 dmonthdum11 |   .1967983   .0422047     4.66   0.000      .114027    .2795695
                 dmonthdum12 |   .2592705    .038875     6.67   0.000     .1830292    .3355117
                 dmonthdum13 |   .1758367   .0414694     4.24   0.000     .0945075    .2571659
                 dmonthdum14 |    .287122   .0439149     6.54   0.000     .2009966    .3732475
                 dmonthdum15 |   .1247605   .0498576     2.50   0.012     .0269804    .2225407
                 dmonthdum16 |   .1612525   .0475644     3.39   0.001     .0679698    .2545352
                 dmonthdum17 |   .0822817   .0417673     1.97   0.049     .0003683    .1641952
                 dmonthdum18 |   .0728162   .0495369     1.47   0.142     -.024335    .1699674
                 dmonthdum19 |   .2150148   .0495519     4.34   0.000     .1178341    .3121954
                 dmonthdum20 |   .0347935     .04813     0.72   0.470    -.0595985    .1291855
                  imonthdum3 |   .0691867   .0306181     2.26   0.024     .0091388    .1292345
                  imonthdum4 |   .1313904    .036362     3.61   0.000     .0600777    .2027031
                  imonthdum5 |   .1051754   .0357069     2.95   0.003     .0351474    .1752034
                  imonthdum6 |   .1327193   .0368957     3.60   0.000       .06036    .2050787
                  imonthdum7 |   .1850708   .0412969     4.48   0.000     .1040798    .2660618
                  imonthdum8 |   .2352391   .0785378     3.00   0.003     .0812117    .3892664
                  imonthdum9 |    .303008   .0703382     4.31   0.000     .1650615    .4409545
                 imonthdum10 |   .0379755   .0898467     0.42   0.673    -.1382308    .2141817
                 imonthdum11 |   .1705556   .0519716     3.28   0.001     .0686294    .2724818
                 imonthdum12 |   .1723251   .0398267     4.33   0.000     .0942173    .2504328
                 imonthdum13 |   .1942365   .0444676     4.37   0.000     .1070272    .2814457
                 imonthdum14 |   .2015618   .0524758     3.84   0.000     .0986469    .3044766
                 imonthdum15 |   .1287505   .0576348     2.23   0.026     .0157178    .2417831
                 imonthdum16 |     .15883   .0466835     3.40   0.001     .0672749     .250385
                 imonthdum17 |   .1231874   .0392927     3.14   0.002      .046127    .2002478
                 imonthdum18 |   .1369079   .0526964     2.60   0.009     .0335603    .2402556
                 imonthdum19 |   .1993931   .0490075     4.07   0.000     .1032802     .295506
                 imonthdum20 |    .042091   .0465604     0.90   0.366    -.0492228    .1334047
Yc4_restrictionsongatherings |   .0061954    .014787     0.42   0.675    -.0228047    .0351954
  Yc6_stayathomerequirements |    .007981    .011718     0.68   0.496    -.0150003    .0309622
        ZLNpc_new_cases_7day |   .0219244   .0057677     3.80   0.000     .0106129     .033236
               out_workforce |   .0003428    .038383     0.01   0.993    -.0749334    .0756191
                    employed |  -.0956544   .0319964    -2.99   0.003    -.1584054   -.0329033
                      income |  -.0030836   .0061527    -0.50   0.616    -.0151502    .0089829
                       _cons |   .6206696   .0532092    11.66   0.000     .5163162    .7250229
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       271           1         270     |
         pid |     14656       14656           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe Mostly_Isol vaccinated dem indep_third dmonthdum3-dmonthdum20 imonthdum3-imonthdum20 Yc4_restrictionsongatherings Yc6
> _stayathomerequirements $controls_main_model $controls_fe_model  [aw=WEIGHT],  a(time ctyfip) vce(cl ctyfip)
(dropped 111 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =    138,270
Absorbing 2 HDFE groups                           F(  57,   2525) =      53.84
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2556
                                                  Adj R-squared   =     0.2399
                                                  Within R-sq.    =     0.0717
Number of clusters (ctyfip)  =      2,526         Root MSE        =     0.4359

                                             (Std. err. adjusted for 2,526 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  vaccinated |  -.0259138    .008064    -3.21   0.001    -.0417266    -.010101
                         dem |   .0608961   .0192033     3.17   0.002     .0232404    .0985519
                 indep_third |   .0398362   .0210854     1.89   0.059    -.0015103    .0811827
                  dmonthdum3 |   .0664245   .0202716     3.28   0.001     .0266739    .1061751
                  dmonthdum4 |   .1744516   .0250852     6.95   0.000     .1252618    .2236413
                  dmonthdum5 |   .1821801   .0252993     7.20   0.000     .1325707    .2317896
                  dmonthdum6 |   .1991375   .0255585     7.79   0.000     .1490196    .2492553
                  dmonthdum7 |   .1918849   .0286259     6.70   0.000     .1357523    .2480174
                  dmonthdum8 |   .1711845   .0432733     3.96   0.000     .0863296    .2560393
                  dmonthdum9 |   .1755047   .0434362     4.04   0.000     .0903304    .2606789
                 dmonthdum10 |   .2161364   .0467248     4.63   0.000     .1245136    .3077592
                 dmonthdum11 |   .2180191   .0314953     6.92   0.000     .1562598    .2797784
                 dmonthdum12 |   .2075893   .0274214     7.57   0.000     .1538186      .26136
                 dmonthdum13 |   .2096091   .0296191     7.08   0.000     .1515289    .2676893
                 dmonthdum14 |    .218939   .0288051     7.60   0.000     .1624551    .2754229
                 dmonthdum15 |   .0799049   .0279898     2.85   0.004     .0250197    .1347902
                 dmonthdum16 |   .0900017   .0270288     3.33   0.001     .0370008    .1430026
                 dmonthdum17 |   .0571027    .026739     2.14   0.033     .0046701    .1095352
                 dmonthdum18 |   .0141073   .0269818     0.52   0.601    -.0388014     .067016
                 dmonthdum19 |   .0698281   .0288113     2.42   0.015     .0133319    .1263244
                 dmonthdum20 |   .0498178    .028204     1.77   0.077    -.0054875    .1051231
                  imonthdum3 |    .031118   .0229272     1.36   0.175    -.0138401    .0760761
                  imonthdum4 |   .0828272   .0265908     3.11   0.002     .0306852    .1349692
                  imonthdum5 |   .0939422   .0271722     3.46   0.001     .0406601    .1472242
                  imonthdum6 |   .1062262   .0268716     3.95   0.000     .0535336    .1589188
                  imonthdum7 |   .1193313   .0308246     3.87   0.000     .0588872    .1797754
                  imonthdum8 |   .1042277   .0484855     2.15   0.032     .0091523     .199303
                  imonthdum9 |   .1813856    .048713     3.72   0.000      .085864    .2769071
                 imonthdum10 |   .0566251    .051206     1.11   0.269    -.0437849    .1570352
                 imonthdum11 |   .1734551   .0356636     4.86   0.000     .1035223     .243388
                 imonthdum12 |    .077039   .0325214     2.37   0.018     .0132677    .1408103
                 imonthdum13 |   .1290483   .0318534     4.05   0.000     .0665869    .1915097
                 imonthdum14 |   .1216174   .0302926     4.01   0.000     .0622166    .1810183
                 imonthdum15 |   .0923275   .0308163     3.00   0.003     .0318996    .1527554
                 imonthdum16 |   .0704183   .0278546     2.53   0.012     .0157982    .1250384
                 imonthdum17 |   .0595572   .0267004     2.23   0.026     .0072002    .1119142
                 imonthdum18 |   .0632641   .0300843     2.10   0.036     .0042716    .1222566
                 imonthdum19 |   .0410163    .031088     1.32   0.187    -.0199443    .1019768
                 imonthdum20 |   .0485991   .0285453     1.70   0.089    -.0073755    .1045737
Yc4_restrictionsongatherings |   -.000463   .0094012    -0.05   0.961    -.0188979    .0179718
  Yc6_stayathomerequirements |   .0075764   .0079202     0.96   0.339    -.0079543    .0231071
                        male |  -.0454627   .0061862    -7.35   0.000    -.0575932   -.0333322
                       age10 |  -.0177129    .003086    -5.74   0.000    -.0237642   -.0116616
                  age_group4 |   .0097127    .010854     0.89   0.371    -.0115709    .0309963
             live_w_children |  -.0353051   .0074194    -4.76   0.000    -.0498538   -.0207564
                     somecol |   .0212803   .0084951     2.51   0.012     .0046223    .0379384
                          ba |   .0850993   .0110999     7.67   0.000     .0633335    .1068651
                        grad |   .1102112   .0099725    11.05   0.000     .0906561    .1297663
                     AmerInd |  -.0232389   .0434479    -0.53   0.593     -.108436    .0619582
                       Asian |   .0059311   .0300564     0.20   0.844    -.0530066    .0648687
                       Black |  -.0323266   .0120469    -2.68   0.007    -.0559494   -.0087037
                        Hisp |   .0044253   .0108881     0.41   0.684    -.0169254    .0257759
                 Multiracial |  -.0240701   .0179953    -1.34   0.181    -.0593571    .0112169
        ZLNpc_new_cases_7day |    .021554   .0035232     6.12   0.000     .0146454    .0284626
               out_workforce |    .018523    .014755     1.26   0.209    -.0104101    .0474562
                    employed |  -.1670318   .0132002   -12.65   0.000    -.1929162   -.1411474
                      income |   .0044097   .0016345     2.70   0.007     .0012046    .0076148
                       _cons |   .5392865   .0231742    23.27   0.000      .493844    .5847289
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       284           1         283     |
      ctyfip |      2526        2526           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(dmonthdum3 dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10  
>    dmonthdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum1
> 8     dmonthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("MostlyIsolate", replace) ///
> title("Mostly Isolating (base month March 2020)") xtitle("Pandemic Month")
(file MostlyIsolate.gph not found)
file MostlyIsolate.gph saved

. 
. *Worn masks
. 
. tab month_number if worn_mask!=.

month_numbe |
          r |      Freq.     Percent        Cum.
------------+-----------------------------------
          4 |     25,977       19.41       19.41
          5 |     17,732       13.25       32.66
          6 |     15,770       11.78       44.45
          7 |     16,351       12.22       56.67
          8 |     11,273        8.42       65.09
          9 |      2,730        2.04       67.13
         10 |      2,972        2.22       69.35
         11 |      2,976        2.22       71.57
         12 |      3,053        2.28       73.86
         13 |      4,138        3.09       76.95
         14 |      3,757        2.81       79.76
         15 |      3,901        2.92       82.67
         16 |      3,726        2.78       85.46
         17 |      3,569        2.67       88.12
         18 |      4,839        3.62       91.74
         19 |      3,473        2.60       94.33
         20 |      3,551        2.65       96.99
         21 |      4,032        3.01      100.00
------------+-----------------------------------
      Total |    133,820      100.00

. 
. estimates clear

. reghdfe worn_mask vaccinated dem indep_third dmonthdum4-dmonthdum20 imonthdum2 imonthdum4-imonthdum20  $controls_fe_model  Y3
> h6_facialcoverings [aw=WEIGHT]  if minmonthmask==4  , a(time pid) vce(cl ctyfip)
(dropped 3840 singleton observations)
(MWFE estimator converged in 11 iterations)
note: imonthdum2 omitted because of collinearity

HDFE Linear regression                            Number of obs   =     65,879
Absorbing 2 HDFE groups                           F(  42,   2149) =       8.30
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6228
                                                  Adj R-squared   =     0.4468
                                                  Within R-sq.    =     0.0212
Number of clusters (ctyfip)  =      2,150         Root MSE        =     0.3038

                                     (Std. err. adjusted for 2,150 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
          vaccinated |  -.0177722   .0121664    -1.46   0.144    -.0416314    .0060871
                 dem |  -.0735687   .0269635    -2.73   0.006     -.126446   -.0206914
         indep_third |   -.076885    .025244    -3.05   0.002    -.1263902   -.0273797
          dmonthdum4 |   .0594942   .0274222     2.17   0.030     .0057174     .113271
          dmonthdum5 |   .0867699   .0245146     3.54   0.000     .0386952    .1348447
          dmonthdum6 |  -.0148294   .0225467    -0.66   0.511     -.059045    .0293862
          dmonthdum7 |  -.0537185    .023982    -2.24   0.025    -.1007488   -.0066882
          dmonthdum8 |  -.0817219   .0410733    -1.99   0.047    -.1622694   -.0011745
          dmonthdum9 |  -.0068395      .0421    -0.16   0.871    -.0894004    .0757214
         dmonthdum10 |  -.0281082   .0322715    -0.87   0.384    -.0913948    .0351784
         dmonthdum11 |   .0153144   .0287092     0.53   0.594    -.0409863    .0716151
         dmonthdum12 |  -.0739191   .0275561    -2.68   0.007    -.1279585   -.0198797
         dmonthdum13 |   -.005666   .0315728    -0.18   0.858    -.0675825    .0562505
         dmonthdum14 |  -.0227433   .0291758    -0.78   0.436    -.0799591    .0344724
         dmonthdum15 |   .0254601   .0335133     0.76   0.448    -.0402617     .091182
         dmonthdum16 |   .1294994   .0359249     3.60   0.000     .0590482    .1999506
         dmonthdum17 |   .2182437   .0343978     6.34   0.000     .1507873    .2857002
         dmonthdum18 |   .2185597   .0451661     4.84   0.000     .1299859    .3071335
         dmonthdum19 |   .2596676   .0385742     6.73   0.000     .1840208    .3353143
         dmonthdum20 |   .2346506   .0328269     7.15   0.000     .1702749    .2990264
          imonthdum2 |          0  (omitted)
          imonthdum4 |   .0665139   .0319828     2.08   0.038     .0037933    .1292344
          imonthdum5 |   .0492779   .0265152     1.86   0.063    -.0027202    .1012761
          imonthdum6 |   .0281589   .0258759     1.09   0.277    -.0225854    .0789033
          imonthdum7 |  -.0173044    .027914    -0.62   0.535    -.0720458    .0374369
          imonthdum8 |  -.0941604   .0458731    -2.05   0.040    -.1841206   -.0042001
          imonthdum9 |  -.0217727   .0526409    -0.41   0.679    -.1250051    .0814596
         imonthdum10 |   .0439057   .0412171     1.07   0.287    -.0369239    .1247353
         imonthdum11 |   .0970736   .0369256     2.63   0.009     .0246599    .1694873
         imonthdum12 |  -.0202189    .030319    -0.67   0.505    -.0796767    .0392388
         imonthdum13 |   .0376321   .0368334     1.02   0.307    -.0346008    .1098649
         imonthdum14 |   .0085289   .0329087     0.26   0.796    -.0560072    .0730651
         imonthdum15 |   .0462628   .0385642     1.20   0.230    -.0293643    .1218899
         imonthdum16 |   .0894244   .0423669     2.11   0.035       .00634    .1725087
         imonthdum17 |   .0715553   .0423561     1.69   0.091     -.011508    .1546186
         imonthdum18 |   .1141831   .0515371     2.22   0.027     .0131154    .2152508
         imonthdum19 |   .1373432   .0459226     2.99   0.003     .0472858    .2274006
         imonthdum20 |   .0913772   .0382568     2.39   0.017     .0163531    .1664013
ZLNpc_new_cases_7day |   .0361293   .0051635     7.00   0.000     .0260034    .0462553
       out_workforce |   .0025236   .0271959     0.09   0.926    -.0508094    .0558566
            employed |   .0206343   .0237833     0.87   0.386    -.0260064    .0672751
              income |  -.0051418   .0044268    -1.16   0.246    -.0138231    .0035395
Y3h6_facialcoverings |   .0176751    .009256     1.91   0.056    -.0004765    .0358268
               _cons |   .8254425   .0371305    22.23   0.000      .752627    .8982581
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       265           1         264     |
         pid |     20655       20655           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe worn_mask vaccinated dem indep_third dmonthdum4-dmonthdum20 imonthdum2 imonthdum4-imonthdum20 $controls_fe_model  Y3h
> 6_facialcoverings $controls_main_model [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 121 singleton observations)
(MWFE estimator converged in 8 iterations)
note: imonthdum2 omitted because of collinearity

HDFE Linear regression                            Number of obs   =    118,251
Absorbing 2 HDFE groups                           F(  54,   2500) =      38.40
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3072
                                                  Adj R-squared   =     0.2903
                                                  Within R-sq.    =     0.0836
Number of clusters (ctyfip)  =      2,501         Root MSE        =     0.3340

                                     (Std. err. adjusted for 2,501 clusters in ctyfip)
--------------------------------------------------------------------------------------
                     |               Robust
           worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
          vaccinated |   .1096539   .0079267    13.83   0.000     .0941102    .1251975
                 dem |   .1700619   .0144012    11.81   0.000     .1418223    .1983015
         indep_third |   .0822354   .0160169     5.13   0.000     .0508277    .1136431
          dmonthdum4 |   .0367342   .0187152     1.96   0.050     .0000352    .0734332
          dmonthdum5 |   .0588334   .0194858     3.02   0.003     .0206234    .0970433
          dmonthdum6 |  -.0298521   .0185172    -1.61   0.107    -.0661627    .0064586
          dmonthdum7 |  -.0774191   .0190959    -4.05   0.000    -.1148645   -.0399736
          dmonthdum8 |  -.1055059   .0276553    -3.82   0.000    -.1597355   -.0512763
          dmonthdum9 |  -.0058695   .0324183    -0.18   0.856     -.069439       .0577
         dmonthdum10 |  -.0276334   .0282444    -0.98   0.328    -.0830182    .0277514
         dmonthdum11 |  -.0465332   .0225884    -2.06   0.039    -.0908271   -.0022394
         dmonthdum12 |  -.0787863   .0214655    -3.67   0.000    -.1208782   -.0366944
         dmonthdum13 |  -.0430958   .0228106    -1.89   0.059    -.0878255    .0016338
         dmonthdum14 |  -.0372143   .0203213    -1.83   0.067    -.0770626    .0026339
         dmonthdum15 |  -.0206444   .0254448    -0.81   0.417    -.0705394    .0292506
         dmonthdum16 |   .0753928   .0248727     3.03   0.002     .0266196     .124166
         dmonthdum17 |   .1608205   .0228428     7.04   0.000     .1160277    .2056132
         dmonthdum18 |   .1776627   .0302468     5.87   0.000     .1183512    .2369741
         dmonthdum19 |   .2312648   .0270449     8.55   0.000     .1782322    .2842975
         dmonthdum20 |   .1957225    .023994     8.16   0.000     .1486723    .2427726
          imonthdum2 |          0  (omitted)
          imonthdum4 |   .0171408   .0240948     0.71   0.477     -.030107    .0643887
          imonthdum5 |   .0238798   .0231657     1.03   0.303    -.0215462    .0693059
          imonthdum6 |  -.0020343   .0215549    -0.09   0.925    -.0443016     .040233
          imonthdum7 |   -.010862   .0223208    -0.49   0.627    -.0546311    .0329071
          imonthdum8 |  -.0993812   .0380767    -2.61   0.009    -.1740462   -.0247161
          imonthdum9 |  -.0171943   .0436256    -0.39   0.694    -.1027403    .0683517
         imonthdum10 |  -.0092253   .0363523    -0.25   0.800    -.0805089    .0620584
         imonthdum11 |   .0010798   .0264027     0.04   0.967    -.0506936    .0528532
         imonthdum12 |  -.0287279   .0253356    -1.13   0.257    -.0784088    .0209529
         imonthdum13 |  -.0351374    .027286    -1.29   0.198    -.0886428     .018368
         imonthdum14 |   .0186007   .0239573     0.78   0.438    -.0283775     .065579
         imonthdum15 |  -.0131695    .027912    -0.47   0.637    -.0679025    .0415636
         imonthdum16 |   .0370344   .0308407     1.20   0.230    -.0234416    .0975104
         imonthdum17 |   .0918602   .0290828     3.16   0.002     .0348313    .1488891
         imonthdum18 |   .0818597    .034293     2.39   0.017      .014614    .1491054
         imonthdum19 |   .0918258   .0323721     2.84   0.005      .028347    .1553046
         imonthdum20 |   .0991692   .0282484     3.51   0.000     .0437766    .1545617
ZLNpc_new_cases_7day |    .032084   .0036617     8.76   0.000     .0249038    .0392642
       out_workforce |   .0001744   .0117465     0.01   0.988    -.0228594    .0232082
            employed |  -.0090186   .0100319    -0.90   0.369    -.0286903    .0106532
              income |  -.0015641   .0012863    -1.22   0.224    -.0040865    .0009582
Y3h6_facialcoverings |   .0163688   .0066245     2.47   0.014     .0033787    .0293589
                male |    -.04827   .0048134   -10.03   0.000    -.0577086   -.0388314
               age10 |   .0099795   .0028211     3.54   0.000     .0044475    .0155116
          age_group4 |   .0148183   .0097724     1.52   0.130    -.0043445    .0339811
     live_w_children |  -.0192005   .0059241    -3.24   0.001    -.0308172   -.0075838
             somecol |   .0315047   .0073645     4.28   0.000     .0170634    .0459459
                  ba |   .0632176   .0077767     8.13   0.000     .0479681    .0784671
                grad |   .0701417   .0072226     9.71   0.000     .0559787    .0843046
             AmerInd |   .0217027    .043075     0.50   0.614    -.0627637    .1061692
               Asian |    .032011   .0164992     1.94   0.052    -.0003424    .0643644
               Black |   .0199856   .0081758     2.44   0.015     .0039535    .0360176
                Hisp |   .0072442   .0070829     1.02   0.307    -.0066447    .0211331
         Multiracial |  -.0140981   .0165972    -0.85   0.396    -.0466438    .0184477
               _cons |   .6256891   .0177517    35.25   0.000     .5908795    .6604987
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       266           1         265     |
      ctyfip |      2501        2501           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Mask", replace) ///
> title("Worn mask (base month April 2020)") xtitle("Pandemic Month")
(file Mask.gph not found)
file Mask.gph saved

. 
. 
. *Very Worried Ill
. 
. estimates clear

. reghdfe v_worry_ill vaccinated dem indep_third  dmonthdum4-dmonthdum20 imonthdum2 imonthdum4-imonthdum20  $controls_fe_model 
> Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT]  if minmonthworry==4  , a(time pid) vce(cl ctyfip)
(dropped 3188 singleton observations)
(MWFE estimator converged in 11 iterations)
note: imonthdum2 omitted because of collinearity

HDFE Linear regression                            Number of obs   =     53,814
Absorbing 2 HDFE groups                           F(  43,   2030) =       5.02
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6427
                                                  Adj R-squared   =     0.4744
                                                  Within R-sq.    =     0.0154
Number of clusters (ctyfip)  =      2,031         Root MSE        =     0.2221

                                             (Std. err. adjusted for 2,031 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  vaccinated |  -.0611267   .0086927    -7.03   0.000    -.0781742   -.0440791
                         dem |   .0200462   .0174298     1.15   0.250    -.0141359    .0542283
                 indep_third |  -.0236089   .0117349    -2.01   0.044    -.0466226   -.0005952
                  dmonthdum4 |  -.0281229   .0179471    -1.57   0.117    -.0633196    .0070738
                  dmonthdum5 |  -.0203404   .0157047    -1.30   0.195    -.0511394    .0104586
                  dmonthdum6 |   .0463352   .0189009     2.45   0.014     .0092681    .0834024
                  dmonthdum7 |   .0576515   .0177579     3.25   0.001     .0228259    .0924771
                  dmonthdum8 |   .0679626   .0377652     1.80   0.072       -.0061    .1420252
                  dmonthdum9 |   .1028825   .0317774     3.24   0.001     .0405627    .1652023
                 dmonthdum10 |   .0781488   .0448957     1.74   0.082    -.0098977    .1661952
                 dmonthdum11 |   .0218186   .0266217     0.82   0.413    -.0303901    .0740274
                 dmonthdum12 |   .0090724   .0221075     0.41   0.682    -.0342834    .0524281
                 dmonthdum13 |   .0209903   .0269224     0.78   0.436    -.0318081    .0737887
                 dmonthdum14 |  -.0437818   .0216516    -2.02   0.043    -.0862436   -.0013201
                 dmonthdum15 |  -.0415228   .0233913    -1.78   0.076    -.0873962    .0043507
                 dmonthdum16 |  -.1044256   .0229539    -4.55   0.000    -.1494413   -.0594099
                 dmonthdum17 |  -.0575003   .0196027    -2.93   0.003    -.0959438   -.0190567
                 dmonthdum18 |  -.0600398   .0281572    -2.13   0.033    -.1152599   -.0048197
                 dmonthdum19 |  -.0368933   .0276041    -1.34   0.182    -.0910287    .0172421
                 dmonthdum20 |  -.0492371   .0235933    -2.09   0.037    -.0955068   -.0029675
                  imonthdum2 |          0  (omitted)
                  imonthdum4 |   .0214352   .0199047     1.08   0.282    -.0176005     .060471
                  imonthdum5 |   .0356065   .0166085     2.14   0.032     .0030349     .068178
                  imonthdum6 |   .0606719   .0192851     3.15   0.002     .0228513    .0984925
                  imonthdum7 |   .0297745   .0185216     1.61   0.108    -.0065488    .0660978
                  imonthdum8 |   .0304215   .0329111     0.92   0.355    -.0341215    .0949645
                  imonthdum9 |   .0780887   .0367499     2.12   0.034     .0060172    .1501602
                 imonthdum10 |   .0175915   .0397189     0.44   0.658    -.0603025    .0954856
                 imonthdum11 |  -.0068845   .0243511    -0.28   0.777    -.0546403    .0408714
                 imonthdum12 |   .0371887   .0227998     1.63   0.103    -.0075248    .0819021
                 imonthdum13 |   .0383404   .0217919     1.76   0.079    -.0043964    .0810772
                 imonthdum14 |   .0057761   .0179951     0.32   0.748    -.0295147    .0410669
                 imonthdum15 |   .0479993   .0232338     2.07   0.039     .0024347    .0935638
                 imonthdum16 |   .0081947   .0224179     0.37   0.715    -.0357698    .0521592
                 imonthdum17 |   .0135527   .0218098     0.62   0.534    -.0292193    .0563246
                 imonthdum18 |    .028584   .0221813     1.29   0.198    -.0149164    .0720844
                 imonthdum19 |   .0206402   .0209828     0.98   0.325    -.0205099    .0617904
                 imonthdum20 |   .0150806   .0205837     0.73   0.464    -.0252867    .0554479
        ZLNpc_new_cases_7day |    .010057   .0036205     2.78   0.006     .0029567    .0171573
               out_workforce |  -.0365516    .022359    -1.63   0.102    -.0804006    .0072975
                    employed |  -.0326532   .0200028    -1.63   0.103    -.0718814    .0065751
                      income |  -.0015911   .0034422    -0.46   0.644    -.0083417    .0051595
Yc4_restrictionsongatherings |  -.0017813   .0110163    -0.16   0.872    -.0233857     .019823
  Yc6_stayathomerequirements |   .0107363    .007681     1.40   0.162    -.0043272    .0257998
                       _cons |   .1392088   .0260558     5.34   0.000     .0881098    .1903077
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       253           1         252     |
         pid |     16938       16938           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. reghdfe v_worry_ill vaccinated dem indep_third dmonthdum4-dmonthdum20 imonthdum2 imonthdum4-imonthdum20 $controls_fe_model Yc
> 4_restrictionsongatherings Yc6_stayathomerequirements $controls_main_model  [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 126 singleton observations)
(MWFE estimator converged in 8 iterations)
note: imonthdum2 omitted because of collinearity

HDFE Linear regression                            Number of obs   =    114,068
Absorbing 2 HDFE groups                           F(  55,   2488) =      17.47
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1361
                                                  Adj R-squared   =     0.1143
                                                  Within R-sq.    =     0.0382
Number of clusters (ctyfip)  =      2,489         Root MSE        =     0.2871

                                             (Std. err. adjusted for 2,489 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  vaccinated |  -.0181498   .0048393    -3.75   0.000    -.0276394   -.0086603
                         dem |   .1044896   .0120599     8.66   0.000     .0808411     .128138
                 indep_third |   .0382109   .0117997     3.24   0.001     .0150726    .0613491
                  dmonthdum4 |   .0066248    .014894     0.44   0.657    -.0225812    .0358308
                  dmonthdum5 |  -.0024305   .0144169    -0.17   0.866    -.0307009    .0258398
                  dmonthdum6 |   .0673423   .0160184     4.20   0.000     .0359314    .0987532
                  dmonthdum7 |   .0534609   .0176253     3.03   0.002     .0188991    .0880226
                  dmonthdum8 |   .0280132   .0306162     0.91   0.360    -.0320227    .0880491
                  dmonthdum9 |   .0425169   .0272899     1.56   0.119    -.0109963    .0960301
                 dmonthdum10 |    .078087   .0321799     2.43   0.015     .0149849    .1411891
                 dmonthdum11 |   .0506528    .021179     2.39   0.017     .0091225     .092183
                 dmonthdum12 |   .0402303   .0176956     2.27   0.023     .0055308    .0749299
                 dmonthdum13 |    .036562   .0201023     1.82   0.069     -.002857     .075981
                 dmonthdum14 |  -.0197904    .016664    -1.19   0.235    -.0524671    .0128863
                 dmonthdum15 |  -.0471777   .0146418    -3.22   0.001    -.0758891   -.0184662
                 dmonthdum16 |  -.0755154   .0153273    -4.93   0.000     -.105571   -.0454597
                 dmonthdum17 |  -.0723647   .0138363    -5.23   0.000    -.0994966   -.0452329
                 dmonthdum18 |  -.0695567   .0161919    -4.30   0.000    -.1013077   -.0378057
                 dmonthdum19 |  -.0397213   .0181723    -2.19   0.029    -.0753557   -.0040869
                 dmonthdum20 |  -.0392954   .0157997    -2.49   0.013    -.0702773   -.0083135
                  imonthdum2 |          0  (omitted)
                  imonthdum4 |   .0091507   .0152159     0.60   0.548    -.0206864    .0389878
                  imonthdum5 |   .0122304   .0141815     0.86   0.389    -.0155784    .0400392
                  imonthdum6 |   .0534272   .0164555     3.25   0.001     .0211593    .0856951
                  imonthdum7 |   .0492968   .0167324     2.95   0.003      .016486    .0821077
                  imonthdum8 |  -.0219425   .0253884    -0.86   0.388     -.071727     .027842
                  imonthdum9 |   .0321283   .0283701     1.13   0.258    -.0235032    .0877598
                 imonthdum10 |   .0547491   .0303878     1.80   0.072    -.0048389    .1143371
                 imonthdum11 |    .011673    .021159     0.55   0.581     -.029818    .0531641
                 imonthdum12 |   .0161693   .0173386     0.93   0.351    -.0178303     .050169
                 imonthdum13 |   .0236919   .0181529     1.31   0.192    -.0119044    .0592882
                 imonthdum14 |   .0104748   .0145259     0.72   0.471    -.0180094    .0389589
                 imonthdum15 |   .0126541   .0149215     0.85   0.396    -.0166057    .0419139
                 imonthdum16 |  -.0300895   .0131909    -2.28   0.023    -.0559558   -.0042232
                 imonthdum17 |  -.0140789   .0134641    -1.05   0.296     -.040481    .0123231
                 imonthdum18 |  -.0038818    .015129    -0.26   0.798    -.0335485    .0257849
                 imonthdum19 |  -.0215656   .0162517    -1.33   0.185    -.0534338    .0103025
                 imonthdum20 |   .0092654   .0156414     0.59   0.554    -.0214062    .0399369
        ZLNpc_new_cases_7day |   .0115988   .0027751     4.18   0.000      .006157    .0170407
               out_workforce |  -.0333845   .0118733    -2.81   0.005    -.0566672   -.0101019
                    employed |  -.0360684     .01129    -3.19   0.001    -.0582071   -.0139297
                      income |  -.0054148   .0011275    -4.80   0.000    -.0076256   -.0032039
Yc4_restrictionsongatherings |  -.0029803   .0067571    -0.44   0.659    -.0162305    .0102699
  Yc6_stayathomerequirements |   .0016909   .0056186     0.30   0.763    -.0093266    .0127085
                        male |  -.0408585   .0052145    -7.84   0.000    -.0510838   -.0306333
                       age10 |  -.0011214   .0022783    -0.49   0.623    -.0055889    .0033461
                  age_group4 |  -.0247163   .0089939    -2.75   0.006    -.0423525   -.0070801
             live_w_children |   .0016547   .0053871     0.31   0.759     -.008909    .0122184
                     somecol |   .0121941   .0062498     1.95   0.051    -.0000613    .0244494
                          ba |    .001151   .0071825     0.16   0.873    -.0129334    .0152353
                        grad |   .0120116   .0075248     1.60   0.111    -.0027438    .0267671
                     AmerInd |   .0103208    .025412     0.41   0.685      -.03951    .0601516
                       Asian |   .0294268   .0299382     0.98   0.326    -.0292795    .0881331
                       Black |  -.0088028    .009389    -0.94   0.349    -.0272139    .0096083
                        Hisp |   .0187793   .0087454     2.15   0.032     .0016303    .0359284
                 Multiracial |   .0227213   .0127541     1.78   0.075    -.0022886    .0477311
                       _cons |   .1300086   .0167064     7.78   0.000     .0972488    .1627683
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       262           1         261     |
      ctyfip |      2489        2489           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Worry", replace) ///
> title("Very worried about COVID (base month April 2020)") xtitle("Pandemic Month")
(file Worry.gph not found)
file Worry.gph saved

. 
. 
. *Mostly remote
. 
. estimates clear

. reghdfe mostly_remote vaccinated dem indep_third dmonthdum5-dmonthdum20 imonthdum5-imonthdum20  ZLNpc_new_cases_7day  live_w_
> children income Yc4_restrictionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing  [aw=WEIGHT]  if (minmonthmostly
> _remote==4 | minmonthmostly_remote==5)  &  employed==1, a(time pid) vce(cl ctyfip)
(dropped 2119 singleton observations)
(MWFE estimator converged in 14 iterations)
note: live_w_children is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     21,534
Absorbing 2 HDFE groups                           F(  40,   1437) =       1.56
Statistics robust to heteroskedasticity           Prob > F        =     0.0142
                                                  R-squared       =     0.8043
                                                  Adj R-squared   =     0.7027
                                                  Within R-sq.    =     0.0071
Number of clusters (ctyfip)  =      1,438         Root MSE        =     0.2724

                                             (Std. err. adjusted for 1,438 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  vaccinated |  -.0729322   .0152792    -4.77   0.000    -.1029042   -.0429603
                         dem |   .0061901   .0320694     0.19   0.847    -.0567177    .0690979
                 indep_third |   .0037931   .0267978     0.14   0.887    -.0487739      .05636
                  dmonthdum5 |  -.0033621   .0314359    -0.11   0.915    -.0650272     .058303
                  dmonthdum6 |  -.0006066   .0304052    -0.02   0.984    -.0602499    .0590367
                  dmonthdum7 |   .0286282   .0364412     0.79   0.432    -.0428555    .1001119
                  dmonthdum8 |  -.0590082   .0628886    -0.94   0.348    -.1823714     .064355
                  dmonthdum9 |  -.0630959   .0608594    -1.04   0.300    -.1824787    .0562869
                 dmonthdum10 |   .0662138   .0717511     0.92   0.356    -.0745343    .2069619
                 dmonthdum11 |  -.0647009   .0404875    -1.60   0.110    -.1441219      .01472
                 dmonthdum12 |  -.0572993   .0430216    -1.33   0.183    -.1416912    .0270926
                 dmonthdum13 |  -.0168697   .0362542    -0.47   0.642    -.0879865    .0542471
                 dmonthdum14 |   .0410425    .042599     0.96   0.335    -.0425203    .1246054
                 dmonthdum15 |  -.0559369    .050049    -1.12   0.264    -.1541139    .0422401
                 dmonthdum16 |   .0063047   .0463051     0.14   0.892     -.084528    .0971375
                 dmonthdum17 |   .0391291   .0467077     0.84   0.402    -.0524936    .1307517
                 dmonthdum18 |   .0144008   .0534421     0.27   0.788     -.090432    .1192337
                 dmonthdum19 |   .0495485   .0616226     0.80   0.421    -.0713313    .1704283
                 dmonthdum20 |  -.0679642   .0498193    -1.36   0.173    -.1656905    .0297621
                  imonthdum5 |  -.0205936   .0351123    -0.59   0.558    -.0894705    .0482833
                  imonthdum6 |  -.0221316   .0330566    -0.67   0.503     -.086976    .0427127
                  imonthdum7 |  -.0136443   .0324739    -0.42   0.674    -.0773457    .0500571
                  imonthdum8 |  -.0961409   .0666738    -1.44   0.150    -.2269293    .0346475
                  imonthdum9 |  -.0947797   .0588761    -1.61   0.108     -.210272    .0207127
                 imonthdum10 |   .0535692   .0637122     0.84   0.401    -.0714096    .1785481
                 imonthdum11 |  -.0577681   .0434055    -1.33   0.183    -.1429132    .0273769
                 imonthdum12 |  -.0537275    .048499    -1.11   0.268     -.148864     .041409
                 imonthdum13 |  -.0338699   .0430881    -0.79   0.432    -.1183922    .0506524
                 imonthdum14 |   .0015791   .0430476     0.04   0.971    -.0828638    .0860219
                 imonthdum15 |  -.0249934   .0574563    -0.43   0.664    -.1377005    .0877138
                 imonthdum16 |   .0310743   .0544624     0.57   0.568    -.0757601    .1379086
                 imonthdum17 |    .028363   .0452574     0.63   0.531    -.0604147    .1171407
                 imonthdum18 |   .0506068   .0531454     0.95   0.341     -.053644    .1548577
                 imonthdum19 |   .0168743   .0642047     0.26   0.793    -.1090706    .1428192
                 imonthdum20 |  -.1092502   .0507832    -2.15   0.032    -.2088673   -.0096331
        ZLNpc_new_cases_7day |  -.0042791   .0074471    -0.57   0.566    -.0188875    .0103293
             live_w_children |          0  (omitted)
                      income |   .0007796   .0068613     0.11   0.910    -.0126795    .0142388
Yc4_restrictionsongatherings |  -.0157058    .016649    -0.94   0.346    -.0483646    .0169531
  Yc6_stayathomerequirements |  -.0042764   .0125557    -0.34   0.733    -.0289058     .020353
        Yc2_workplaceclosing |    .005752   .0120389     0.48   0.633    -.0178637    .0293677
                       _cons |     .49498   .0514401     9.62   0.000     .3940742    .5958859
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       236           1         235     |
         pid |      7085        7085           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. reghdfe mostly_remote vaccinated dem indep_third dmonthdum5-dmonthdum20 imonthdum5-imonthdum20 ZLNpc_new_cases_7day  live_w_c
> hildren income Yc4_restrictionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing  $controls_main_model  if  employ
> ed==1 [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 242 singleton observations)
(MWFE estimator converged in 8 iterations)
note: live_w_children omitted because of collinearity

HDFE Linear regression                            Number of obs   =     51,845
Absorbing 2 HDFE groups                           F(  52,   1979) =      40.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3185
                                                  Adj R-squared   =     0.2873
                                                  Within R-sq.    =     0.1241
Number of clusters (ctyfip)  =      1,980         Root MSE        =     0.4190

                                             (Std. err. adjusted for 1,980 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                  vaccinated |  -.0494456   .0109611    -4.51   0.000    -.0709422    -.027949
                         dem |   .1380564   .0208153     6.63   0.000     .0972341    .1788787
                 indep_third |   .0766519   .0220513     3.48   0.001     .0334057    .1198981
                  dmonthdum5 |    .008285   .0287061     0.29   0.773    -.0480123    .0645823
                  dmonthdum6 |   .0041241   .0274684     0.15   0.881     -.049746    .0579943
                  dmonthdum7 |   .0142057   .0319938     0.44   0.657    -.0485394    .0769508
                  dmonthdum8 |   .0898311   .0545408     1.65   0.100    -.0171323    .1967945
                  dmonthdum9 |  -.0368008   .0614691    -0.60   0.549    -.1573516    .0837501
                 dmonthdum10 |   .0474833    .052983     0.90   0.370    -.0564251    .1513917
                 dmonthdum11 |   .0107352   .0392661     0.27   0.785     -.066272    .0877424
                 dmonthdum12 |  -.0289363   .0367803    -0.79   0.432    -.1010684    .0431958
                 dmonthdum13 |  -.0186344   .0347939    -0.54   0.592    -.0868709     .049602
                 dmonthdum14 |  -.0132583   .0380606    -0.35   0.728    -.0879013    .0613846
                 dmonthdum15 |  -.0570448   .0372384    -1.53   0.126    -.1300755    .0159858
                 dmonthdum16 |  -.0521067   .0348498    -1.50   0.135    -.1204529    .0162395
                 dmonthdum17 |  -.0104806   .0366546    -0.29   0.775    -.0823664    .0614051
                 dmonthdum18 |  -.0392785   .0358602    -1.10   0.274    -.1096062    .0310491
                 dmonthdum19 |   .0025321   .0395535     0.06   0.949    -.0750387     .080103
                 dmonthdum20 |  -.1042342   .0360954    -2.89   0.004    -.1750232   -.0334453
                  imonthdum5 |  -.0045462   .0343073    -0.13   0.895    -.0718285    .0627361
                  imonthdum6 |  -.0213637   .0303833    -0.70   0.482    -.0809503    .0382229
                  imonthdum7 |   .0126542   .0341954     0.37   0.711    -.0544085    .0797169
                  imonthdum8 |   .0783028   .0559208     1.40   0.162    -.0313669    .1879726
                  imonthdum9 |  -.0171435   .0659566    -0.26   0.795    -.1464952    .1122082
                 imonthdum10 |  -.0185364   .0487803    -0.38   0.704    -.1142025    .0771297
                 imonthdum11 |  -.0297697   .0379231    -0.79   0.433    -.1041431    .0446037
                 imonthdum12 |  -.0807813   .0354226    -2.28   0.023    -.1502507   -.0113119
                 imonthdum13 |  -.0466751    .035978    -1.30   0.195    -.1172338    .0238835
                 imonthdum14 |  -.0229813   .0364184    -0.63   0.528    -.0944038    .0484411
                 imonthdum15 |   .0028602   .0391049     0.07   0.942    -.0738308    .0795513
                 imonthdum16 |  -.1121713   .0381662    -2.94   0.003    -.1870215   -.0373211
                 imonthdum17 |    .021918   .0366955     0.60   0.550     -.050048    .0938839
                 imonthdum18 |  -.0202737   .0423021    -0.48   0.632    -.1032351    .0626877
                 imonthdum19 |  -.0093095   .0369276    -0.25   0.801    -.0817306    .0631116
                 imonthdum20 |   -.067456   .0357194    -1.89   0.059    -.1375077    .0025956
        ZLNpc_new_cases_7day |  -.0008049   .0055743    -0.14   0.885    -.0117371    .0101273
             live_w_children |  -.0367405   .0105183    -3.49   0.000    -.0573687   -.0161123
                      income |   .0357375   .0025411    14.06   0.000     .0307539    .0407211
Yc4_restrictionsongatherings |    .008717   .0125765     0.69   0.488    -.0159476    .0333815
  Yc6_stayathomerequirements |   .0058444   .0116461     0.50   0.616    -.0169954    .0286842
        Yc2_workplaceclosing |  -.0058548   .0089448    -0.65   0.513    -.0233971    .0116875
                        male |  -.0991733   .0103655    -9.57   0.000    -.1195017   -.0788449
                       age10 |  -.0170127   .0045553    -3.73   0.000    -.0259464   -.0080789
                  age_group4 |   .0128928   .0194018     0.66   0.506    -.0251572    .0509429
             live_w_children |          0  (omitted)
                     somecol |   .0555632   .0145702     3.81   0.000     .0269885    .0841378
                          ba |   .2361111   .0173326    13.62   0.000     .2021189    .2701032
                        grad |   .2478112   .0163906    15.12   0.000     .2156666    .2799559
                     AmerInd |   -.100735   .0616942    -1.63   0.103    -.2217273    .0202574
                       Asian |   .0887777   .0488776     1.82   0.069    -.0070793    .1846347
                       Black |   .0177374    .017823     1.00   0.320    -.0172165    .0526913
                        Hisp |  -.0146978   .0196208    -0.75   0.454    -.0531775    .0237818
                 Multiracial |  -.0630398   .0249581    -2.53   0.012    -.1119867   -.0140928
                       _cons |   .1619971   .0307442     5.27   0.000     .1017026    .2222916
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       245           1         244     |
      ctyfip |      1980        1980           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(12 13, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum4      dmonthdum5      dmonthdum6      dmonthdum7      dmonthdum8      dmonthdum9      dmonthdum10     dmont
> hdum11     dmonthdum12     dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dm
> onthdum19     dmonthdum20)), vertical ///
> coeflabels (dmonthdum3="4/20" dmonthdum4="5/20" dmonthdum5="6/20" dmonthdum6="7/20" dmonthdum7="8/20" dmonthdum8="9/20" dmont
> hdum9="10/20" dmonthdum10="11/20" dmonthdum11="12/20" dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4
> /21" dmonthdum16="5/21" dmonthdum17="6/21" dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Remote", replace) ///
> title("Mostly working remote (base month May 2020)") xtitle("Pandemic Month")
(file Remote.gph not found)
file Remote.gph saved

. 
. grc1leg MostlyIsolate.gph Mask.gph Worry.gph Remote.gph   ///
> , imargin(2 2 2 2) row(2) col(2) legendfrom(MostlyIsolate.gph) iscale(*.75) plotregion(color(white)) graphregion(color(white)
> )  

. graph export "figures\Figure S17.png", replace width(2200) height(1600)
file figures\Figure S17.png saved as PNG format

. 
. * Delete the intermediate files
. erase MostlyIsolate.gph 

. erase Mask.gph 

. erase Worry.gph 

. erase Remote.gph

. 
. 
. ******************
. *** Figure S18 *** 
. ******************
. 
. *Change in Partisan Gap in Vaccination Status
. 
. clear

. use "data_gallup.dta"

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(4,143 real changes made)
(3,759 real changes made)
(3,905 real changes made)
(3,731 real changes made)
(3,572 real changes made)
(4,843 real changes made)
(3,475 real changes made)
(3,553 real changes made)
(4,034 real changes made)

. egen minmonthvac=min(month_number) if vaccinated!=., by(pid)
(264 missing values generated)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(30,507 missing values generated)

. egen minmonthisol=min(month_number) if Mostly_Isol!=., by(pid)
(5,890 missing values generated)

. egen minmonthworry=min(month_number) if v_worry_ill!=., by(pid)
(35,223 missing values generated)

. egen minmonthmostly_remote=min(month_number) if mostly_remote!=., by(pid)
(108,466 missing values generated)

. 
. estimates clear

. reghdfe vaccinated dem indep_third dmonthdum13-dmonthdum20 imonthdum13-imonthdum20  $controls_fe_model Yc4_restrictionsongath
> erings Yc6_stayathomerequirements Yc2_workplaceclosing  [aw=WEIGHT]  if minmonthvac==3, a(time pid) vce(cl ctyfip)
(dropped 2355 singleton observations)
(MWFE estimator converged in 11 iterations)

HDFE Linear regression                            Number of obs   =     68,833
Absorbing 2 HDFE groups                           F(  25,   2117) =      21.24
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7191
                                                  Adj R-squared   =     0.6104
                                                  Within R-sq.    =     0.0842
Number of clusters (ctyfip)  =      2,118         Root MSE        =     0.1806

                                             (Std. err. adjusted for 2,118 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                  vaccinated | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |  -.0896976   .0107253    -8.36   0.000    -.1107309   -.0686644
                 indep_third |   -.041587   .0082794    -5.02   0.000    -.0578237   -.0253503
                 dmonthdum13 |   .0959348   .0296713     3.23   0.001     .0377469    .1541227
                 dmonthdum14 |   .1670771   .0340056     4.91   0.000     .1003893     .233765
                 dmonthdum15 |     .31026   .0422644     7.34   0.000      .227376    .3931441
                 dmonthdum16 |   .4258098   .0356949    11.93   0.000      .355809    .4958106
                 dmonthdum17 |   .3654974   .0324695    11.26   0.000     .3018219    .4291728
                 dmonthdum18 |   .4501677   .0370843    12.14   0.000     .3774422    .5228931
                 dmonthdum19 |   .3420214   .0405845     8.43   0.000     .2624318     .421611
                 dmonthdum20 |   .3739376   .0330815    11.30   0.000     .3090621    .4388132
                 imonthdum13 |   .0029905   .0256621     0.12   0.907    -.0473351     .053316
                 imonthdum14 |   .0570938   .0363386     1.57   0.116    -.0141693    .1283569
                 imonthdum15 |   .1371045   .0438938     3.12   0.002      .051025    .2231841
                 imonthdum16 |   .1322273   .0440341     3.00   0.003     .0458726     .218582
                 imonthdum17 |   .1476309   .0385855     3.83   0.000     .0719613    .2233004
                 imonthdum18 |   .1576805   .0456342     3.46   0.001     .0681879    .2471731
                 imonthdum19 |   .0932431   .0461888     2.02   0.044      .002663    .1838233
                 imonthdum20 |   .1507533   .0399434     3.77   0.000      .072421    .2290856
        ZLNpc_new_cases_7day |  -.0023218   .0020022    -1.16   0.246    -.0062483    .0016047
               out_workforce |  -.0022548    .013203    -0.17   0.864     -.028147    .0236374
                    employed |   .0001105   .0111668     0.01   0.992    -.0217887    .0220096
                      income |   .0017055   .0024573     0.69   0.488    -.0031135    .0065245
Yc4_restrictionsongatherings |   .0073843   .0056377     1.31   0.190    -.0036718    .0184403
  Yc6_stayathomerequirements |   .0066455   .0039319     1.69   0.091    -.0010653    .0143564
        Yc2_workplaceclosing |  -.0012063   .0040955    -0.29   0.768    -.0092378    .0068253
                       _cons |   .0985466   .0187513     5.26   0.000     .0617736    .1353196
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       273           1         272     |
         pid |     18909       18909           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. reghdfe vaccinated dem indep_third dmonthdum13-dmonthdum20 imonthdum13-imonthdum20 $controls_fe_model Yc4_restrictionsongathe
> rings Yc6_stayathomerequirements Yc2_workplaceclosing  $controls_main_model   [aw=WEIGHT], a(time ctyfip) vce(cl ctyfip)
(dropped 110 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =    138,518
Absorbing 2 HDFE groups                           F(  37,   2526) =      44.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6337
                                                  Adj R-squared   =     0.6260
                                                  Within R-sq.    =     0.0949
Number of clusters (ctyfip)  =      2,527         Root MSE        =     0.1930

                                             (Std. err. adjusted for 2,527 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                  vaccinated | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |  -.0070421   .0017409    -4.05   0.000    -.0104558   -.0036284
                 indep_third |  -.0001756   .0015824    -0.11   0.912    -.0032786    .0029274
                 dmonthdum13 |   .0746632   .0204908     3.64   0.000     .0344826    .1148437
                 dmonthdum14 |    .132973   .0227478     5.85   0.000     .0883668    .1775791
                 dmonthdum15 |   .3368439   .0293435    11.48   0.000     .2793042    .3943837
                 dmonthdum16 |   .3654471   .0250097    14.61   0.000     .3164054    .4144888
                 dmonthdum17 |   .3895796   .0196954    19.78   0.000     .3509588    .4282004
                 dmonthdum18 |   .4227078   .0253989    16.64   0.000      .372903    .4725126
                 dmonthdum19 |    .353253   .0252714    13.98   0.000     .3036982    .4028078
                 dmonthdum20 |   .3472863   .0218752    15.88   0.000     .3043911    .3901816
                 imonthdum13 |  -.0086922   .0183193    -0.47   0.635    -.0446145    .0272302
                 imonthdum14 |    .012228    .022772     0.54   0.591    -.0324257    .0568816
                 imonthdum15 |   .1020174   .0288438     3.54   0.000     .0454575    .1585773
                 imonthdum16 |   .1345985   .0270865     4.97   0.000     .0814845    .1877124
                 imonthdum17 |   .1521428   .0248094     6.13   0.000     .1034939    .2007916
                 imonthdum18 |   .1250586   .0324517     3.85   0.000      .061424    .1886932
                 imonthdum19 |   .1106692   .0298375     3.71   0.000     .0521608    .1691777
                 imonthdum20 |   .1320234   .0260504     5.07   0.000     .0809411    .1831056
        ZLNpc_new_cases_7day |  -.0022164   .0013665    -1.62   0.105     -.004896    .0004631
               out_workforce |   .0042355   .0046202     0.92   0.359    -.0048242    .0132953
                    employed |   .0049685   .0041766     1.19   0.234    -.0032215    .0131585
                      income |   .0033869   .0004926     6.88   0.000     .0024209    .0043528
Yc4_restrictionsongatherings |   .0000319   .0043211     0.01   0.994    -.0084413    .0085051
  Yc6_stayathomerequirements |   .0059771   .0028168     2.12   0.034     .0004536    .0115007
        Yc2_workplaceclosing |  -.0037117   .0029778    -1.25   0.213    -.0095509    .0021274
                        male |  -.0041695   .0018457    -2.26   0.024    -.0077886   -.0005503
                       age10 |   .0040471   .0009467     4.27   0.000     .0021907    .0059036
                  age_group4 |   .0243622   .0032047     7.60   0.000     .0180781    .0306463
             live_w_children |  -.0160006   .0022287    -7.18   0.000    -.0203708   -.0116305
                     somecol |   .0123402   .0028152     4.38   0.000     .0068199    .0178605
                          ba |   .0234238   .0035224     6.65   0.000     .0165167    .0303309
                        grad |    .031428   .0030994    10.14   0.000     .0253504    .0375056
                     AmerInd |  -.0469507   .0150557    -3.12   0.002    -.0764735   -.0174278
                       Asian |   .0252667   .0131318     1.92   0.054    -.0004835     .051017
                       Black |  -.0221466   .0039563    -5.60   0.000    -.0299045   -.0143887
                        Hisp |  -.0071054   .0025854    -2.75   0.006     -.012175   -.0020357
                 Multiracial |  -.0344634   .0090094    -3.83   0.000    -.0521299   -.0167969
                       _cons |   .0331364   .0077829     4.26   0.000     .0178748     .048398
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |       284           1         283     |
      ctyfip |      2527        2527           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. coefplot (fes, label(With Individual FEs) xline(2 3, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dmonthdum19     dmont
> hdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dmonthdum19     dmont
> hdum20)), vertical ///
> coeflabels ( dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4/21" dmonthdum16="5/21" dmonthdum17="6/21
> " dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Vac", replace) ///
> title("Vaccinated (base month Jan 2021)") xtitle("Pandemic Month")
(file Vac.gph not found)
file Vac.gph saved

. graph export "figures\Figure S18.png", replace
file figures\Figure S18.png saved as PNG format

. 
. * Delete the intermediate files
. erase Vac.gph

. 
. ******************
. *** Figure S19 *** 
. ******************
. 
. *Age, Partisanship, and Vaccination Status
. 
. clear

. use "data_gallup.dta"

. 
. *Determine when respondent was first observed
. gen month_number=month

. forval x=1/9 {
  2. replace month_number=12+`x' if year==2021 & month==`x'
  3. }
(4,143 real changes made)
(3,759 real changes made)
(3,905 real changes made)
(3,731 real changes made)
(3,572 real changes made)
(4,843 real changes made)
(3,475 real changes made)
(3,553 real changes made)
(4,034 real changes made)

. egen minmonthvac=min(month_number) if vaccinated!=., by(pid)
(264 missing values generated)

. egen minmonthmask=min(month_number) if worn_mask!=., by(pid)
(30,507 missing values generated)

. egen minmonthisol=min(month_number) if Mostly_Isol!=., by(pid)
(5,890 missing values generated)

. egen minmonthworry=min(month_number) if v_worry_ill!=., by(pid)
(35,223 missing values generated)

. egen minmonthmostly_remote=min(month_number) if mostly_remote!=., by(pid)
(108,466 missing values generated)

. 
. **Older pop, 65+
. *no individual fixed effects
. reghdfe vaccinated dem indep_third  dmonthdum13-dmonthdum20 imonthdum14-imonthdum20 ZLNpc_new_cases_7day out_workforce employ
> ed live_w_children income   male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial Yc4_restrictionsonga
> therings Yc6_stayathomerequirements Yc2_workplaceclosing [aw=WEIGHT] if month_num>=13 & month_num!=. & age_group4==1, a(time 
> ctyfip) vce(cl ctyfip)
(dropped 444 singleton observations)
(MWFE estimator converged in 8 iterations)
note: age_group4 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =      9,501
Absorbing 2 HDFE groups                           F(  35,   1090) =       8.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4411
                                                  Adj R-squared   =     0.3616
                                                  Within R-sq.    =     0.0512
Number of clusters (ctyfip)  =      1,091         Root MSE        =     0.3883

                                             (Std. err. adjusted for 1,091 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                  vaccinated | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |  -.0077011    .027606    -0.28   0.780    -.0618681    .0464658
                 indep_third |    .010867    .027144     0.40   0.689    -.0423935    .0641274
                 dmonthdum13 |    .165236   .0476344     3.47   0.001     .0717704    .2587015
                 dmonthdum14 |   .2344176   .0442004     5.30   0.000       .14769    .3211451
                 dmonthdum15 |   .1192523   .0491076     2.43   0.015     .0228961    .2156086
                 dmonthdum16 |   .2289938   .0446668     5.13   0.000     .1413513    .3166364
                 dmonthdum17 |   .1835536   .0397997     4.61   0.000     .1054609    .2616463
                 dmonthdum18 |   .2545254   .0465391     5.47   0.000     .1632091    .3458417
                 dmonthdum19 |   .1076096   .0479559     2.24   0.025     .0135134    .2017059
                 dmonthdum20 |    .146871   .0466364     3.15   0.002     .0553637    .2383783
                 imonthdum14 |   .0867583   .0551046     1.57   0.116    -.0213648    .1948813
                 imonthdum15 |   .0068162   .0520124     0.13   0.896    -.0952395    .1088718
                 imonthdum16 |   .0863056   .0487215     1.77   0.077     -.009293    .1819042
                 imonthdum17 |   .0582943    .046442     1.26   0.210    -.0328315    .1494201
                 imonthdum18 |    .064588   .0560708     1.15   0.250    -.0454308    .1746069
                 imonthdum19 |   -.040504   .0537027    -0.75   0.451    -.1458763    .0648683
                 imonthdum20 |   .0467546   .0476763     0.98   0.327    -.0467931    .1403023
        ZLNpc_new_cases_7day |    .006326    .010201     0.62   0.535    -.0136899    .0263419
               out_workforce |   .0315636   .0565813     0.56   0.577    -.0794569    .1425842
                    employed |   .0042181   .0594411     0.07   0.943    -.1124138    .1208499
             live_w_children |  -.0067422    .027906    -0.24   0.809    -.0614977    .0480134
                      income |   .0182182   .0038638     4.72   0.000     .0106368    .0257995
                        male |  -.0178878   .0142453    -1.26   0.209    -.0458391    .0100635
                       age10 |   .0636461   .0136284     4.67   0.000     .0369053    .0903869
                  age_group4 |          0  (omitted)
                     somecol |   .0202031   .0184088     1.10   0.273    -.0159176    .0563238
                          ba |   .0433153   .0246524     1.76   0.079    -.0050562    .0916868
                        grad |   .0728552   .0214575     3.40   0.001     .0307524     .114958
                     AmerInd |  -.1493223   .0924152    -1.62   0.106    -.3306542    .0320095
                       Asian |   .0176451   .0858353     0.21   0.837     -.150776    .1860661
                       Black |  -.0254407   .0254849    -1.00   0.318    -.0754456    .0245643
                        Hisp |  -.0325679   .0300333    -1.08   0.278    -.0914974    .0263617
                 Multiracial |  -.0956293   .0685302    -1.40   0.163    -.2300954    .0388368
Yc4_restrictionsongatherings |  -.0093741   .0208944    -0.45   0.654    -.0503719    .0316237
  Yc6_stayathomerequirements |   .0469079   .0254816     1.84   0.066    -.0030906    .0969063
        Yc2_workplaceclosing |   .0286128   .0205105     1.40   0.163    -.0116316    .0688572
                       _cons |   -.040822   .1240873    -0.33   0.742    -.2842991    .2026551
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        59           1          58     |
      ctyfip |      1091        1091           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. *individual fixed effects
. reghdfe vaccinated dem indep_third  dmonthdum13-dmonthdum20 imonthdum14-imonthdum20  ZLNpc_new_cases_7day out_workforce emplo
> yed income  Yc4_restrictionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing [aw=WEIGHT]  if month_num>=13 & mont
> h_num!=. & age_group4==1, a(time pid) vce(cl ctyfip)
(dropped 4778 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =      5,462
Absorbing 2 HDFE groups                           F(  24,    894) =       3.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7353
                                                  Adj R-squared   =     0.5496
                                                  Within R-sq.    =     0.0244
Number of clusters (ctyfip)  =        895         Root MSE        =     0.3278

                                               (Std. err. adjusted for 895 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                  vaccinated | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |  -.1281288   .0599884    -2.14   0.033    -.2458633   -.0103943
                 indep_third |   .0508448   .0514484     0.99   0.323    -.0501289    .1518186
                 dmonthdum13 |     .23219   .0753993     3.08   0.002     .0842098    .3801703
                 dmonthdum14 |     .27828   .0546378     5.09   0.000     .1710466    .3855134
                 dmonthdum15 |   .1178178   .0652789     1.80   0.071       -.0103    .2459356
                 dmonthdum16 |   .2609911    .056977     4.58   0.000     .1491669    .3728154
                 dmonthdum17 |   .1650479   .0494247     3.34   0.001      .068046    .2620499
                 dmonthdum18 |   .2920037   .0563853     5.18   0.000     .1813407    .4026666
                 dmonthdum19 |   .1572685   .0586846     2.68   0.008     .0420927    .2724442
                 dmonthdum20 |   .1946686   .0570557     3.41   0.001     .0826899    .3066473
                 imonthdum14 |   .0481875   .0647262     0.74   0.457    -.0788455    .1752204
                 imonthdum15 |  -.0283573   .0628842    -0.45   0.652    -.1517751    .0950606
                 imonthdum16 |  -.0145336   .0616906    -0.24   0.814    -.1356089    .1065416
                 imonthdum17 |   .0077471   .0556581     0.14   0.889    -.1014886    .1169828
                 imonthdum18 |   .0907094   .0656984     1.38   0.168    -.0382317    .2196506
                 imonthdum19 |  -.0227588   .0741059    -0.31   0.759    -.1682006    .1226829
                 imonthdum20 |  -.0033075   .0605611    -0.05   0.956     -.122166    .1155509
        ZLNpc_new_cases_7day |   -.017692   .0117942    -1.50   0.134    -.0408396    .0054556
               out_workforce |  -.0221043   .1401976    -0.16   0.875     -.297259    .2530504
                    employed |  -.0019955   .1326439    -0.02   0.988    -.2623252    .2583343
                      income |   .0130384   .0114883     1.13   0.257    -.0095088    .0355856
Yc4_restrictionsongatherings |  -.0200201   .0262552    -0.76   0.446    -.0715491    .0315088
  Yc6_stayathomerequirements |   .0674875   .0323246     2.09   0.037     .0040465    .1309284
        Yc2_workplaceclosing |   .0326817    .024468     1.34   0.182    -.0153397    .0807031
                       _cons |   .5354487   .1511751     3.54   0.000     .2387493    .8321482
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        59           1          58     |
         pid |      2170        2170           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. coefplot (fes, label(With Individual FEs) xline(2 3, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dmonthdum19     dmont
> hdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dmonthdum19     dmont
> hdum20)), vertical ///
> coeflabels ( dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4/21" dmonthdum16="5/21" dmonthdum17="6/21
> " dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> legend(position(6) rows(1)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Vac_65_plus.gph", replace) ///
> title("Vaccination status: Age>=65 (base month Jan 2021)") xtitle("Pandemic Month")
(file Vac_65_plus.gph not found)
file Vac_65_plus.gph saved

. 
. *Younger pop, under 65
. *no individual fixed effects
. reghdfe vaccinated dem indep_third  dmonthdum13-dmonthdum20  imonthdum14-imonthdum20  ZLNpc_new_cases_7day out_workforce empl
> oyed live_w_children income   male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial Yc4_restrictionson
> gatherings Yc6_stayathomerequirements Yc2_workplaceclosing [aw=WEIGHT] if month_num>=13 & month_num!=. & age_group4==0, a(tim
> e ctyfip) vce(cl ctyfip)
(dropped 379 singleton observations)
(MWFE estimator converged in 7 iterations)
note: age_group4 omitted because of collinearity

HDFE Linear regression                            Number of obs   =     20,469
Absorbing 2 HDFE groups                           F(  35,   1459) =      31.11
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4628
                                                  Adj R-squared   =     0.4187
                                                  Within R-sq.    =     0.1200
Number of clusters (ctyfip)  =      1,460         Root MSE        =     0.3810

                                             (Std. err. adjusted for 1,460 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                  vaccinated | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   .0137209   .0202817     0.68   0.499    -.0260634    .0535052
                 indep_third |   .0117707   .0156365     0.75   0.452    -.0189017    .0424432
                 dmonthdum13 |   -.005229   .0263847    -0.20   0.843    -.0569849    .0465269
                 dmonthdum14 |    .080564   .0303965     2.65   0.008     .0209384    .1401895
                 dmonthdum15 |   .3533627   .0373984     9.45   0.000     .2800024    .4267229
                 dmonthdum16 |    .361943   .0335404    10.79   0.000     .2961505    .4277356
                 dmonthdum17 |   .3879601   .0300369    12.92   0.000     .3290401    .4468802
                 dmonthdum18 |   .4213735   .0344582    12.23   0.000     .3537805    .4889664
                 dmonthdum19 |    .363717   .0350826    10.37   0.000     .2948993    .4325346
                 dmonthdum20 |   .3373612   .0328659    10.26   0.000     .2728917    .4018307
                 imonthdum14 |     .00917   .0266468     0.34   0.731    -.0431001      .06144
                 imonthdum15 |   .1334412   .0359619     3.71   0.000     .0628987    .2039837
                 imonthdum16 |   .1612862   .0325515     4.95   0.000     .0974335     .225139
                 imonthdum17 |    .187082   .0327931     5.70   0.000     .1227553    .2514088
                 imonthdum18 |   .1566651   .0378786     4.14   0.000     .0823627    .2309675
                 imonthdum19 |   .1539612   .0377534     4.08   0.000     .0799044     .228018
                 imonthdum20 |   .1556048   .0318265     4.89   0.000     .0931743    .2180353
        ZLNpc_new_cases_7day |  -.0040054   .0072557    -0.55   0.581     -.018238    .0102273
               out_workforce |   .0268941   .0229728     1.17   0.242    -.0181692    .0719574
                    employed |   .0343181   .0202911     1.69   0.091    -.0054848    .0741209
             live_w_children |  -.0669282   .0106086    -6.31   0.000    -.0877379   -.0461186
                      income |   .0141119   .0024495     5.76   0.000      .009307    .0189168
                        male |  -.0328485   .0095809    -3.43   0.001    -.0516424   -.0140547
                       age10 |   .0127845   .0040904     3.13   0.002     .0047609    .0208081
                  age_group4 |          0  (omitted)
                     somecol |   .0359278   .0137666     2.61   0.009     .0089235    .0629322
                          ba |   .0917711   .0176149     5.21   0.000     .0572179    .1263244
                        grad |    .128999   .0158575     8.13   0.000     .0978931    .1601048
                     AmerInd |  -.1171732   .0551697    -2.12   0.034    -.2253935   -.0089528
                       Asian |   .0498807   .0347997     1.43   0.152    -.0183821    .1181436
                       Black |  -.0882833   .0185998    -4.75   0.000    -.1247686    -.051798
                        Hisp |   -.038387    .012605    -3.05   0.002    -.0631129   -.0136612
                 Multiracial |  -.0884241   .0273807    -3.23   0.001    -.1421339   -.0347142
Yc4_restrictionsongatherings |   .0078125   .0143271     0.55   0.586    -.0202914    .0359163
  Yc6_stayathomerequirements |   .0048141   .0159074     0.30   0.762    -.0263897    .0360179
        Yc2_workplaceclosing |  -.0186379   .0121879    -1.53   0.126    -.0425456    .0052699
                       _cons |    .171495   .0311271     5.51   0.000     .1104362    .2325537
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        60           1          59     |
      ctyfip |      1460        1460           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store nofes

. 
. *individual fixed effects
. reghdfe vaccinated dem indep_third  dmonthdum13-dmonthdum20  imonthdum14-imonthdum20  ZLNpc_new_cases_7day out_workforce empl
> oyed income  Yc4_restrictionsongatherings Yc6_stayathomerequirements Yc2_workplaceclosing [aw=WEIGHT]  if month_num>=13 & mon
> th_num!=. & age_group4==0, a(time pid) vce(cl ctyfip)
(dropped 9413 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     12,362
Absorbing 2 HDFE groups                           F(  24,   1238) =      11.60
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7670
                                                  Adj R-squared   =     0.6112
                                                  Within R-sq.    =     0.0606
Number of clusters (ctyfip)  =      1,239         Root MSE        =     0.3113

                                             (Std. err. adjusted for 1,239 clusters in ctyfip)
----------------------------------------------------------------------------------------------
                             |               Robust
                  vaccinated | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |  -.3035229   .0445379    -6.81   0.000    -.3909011   -.2161447
                 indep_third |  -.0959317   .0317773    -3.02   0.003    -.1582751   -.0335883
                 dmonthdum13 |  -.0123386   .0424389    -0.29   0.771    -.0955987    .0709215
                 dmonthdum14 |   .1256249   .0408437     3.08   0.002     .0454943    .2057555
                 dmonthdum15 |   .3443235   .0440975     7.81   0.000     .2578094    .4308376
                 dmonthdum16 |   .3762443   .0420083     8.96   0.000     .2938291    .4586596
                 dmonthdum17 |   .4177451   .0383716    10.89   0.000     .3424645    .4930257
                 dmonthdum18 |   .4093038   .0414186     9.88   0.000     .3280454    .4905622
                 dmonthdum19 |    .414649   .0427086     9.71   0.000     .3308599    .4984382
                 dmonthdum20 |   .3559244   .0404537     8.80   0.000      .276559    .4352897
                 imonthdum14 |   .0039316   .0366663     0.11   0.915    -.0680032    .0758665
                 imonthdum15 |   .1268572   .0406904     3.12   0.002     .0470275    .2066868
                 imonthdum16 |   .1292879   .0376787     3.43   0.001     .0553667    .2032092
                 imonthdum17 |   .1786664   .0364407     4.90   0.000      .107174    .2501588
                 imonthdum18 |   .1160254   .0428656     2.71   0.007     .0319282    .2001226
                 imonthdum19 |   .1691086   .0408643     4.14   0.000     .0889378    .2492795
                 imonthdum20 |   .1305493   .0398635     3.27   0.001     .0523418    .2087568
        ZLNpc_new_cases_7day |    .000219   .0078622     0.03   0.978    -.0152057    .0156438
               out_workforce |  -.0187115   .0444326    -0.42   0.674    -.1058829      .06846
                    employed |  -.0413342   .0370584    -1.12   0.265    -.1140385    .0313701
                      income |  -.0108541   .0072866    -1.49   0.137    -.0251495    .0034414
Yc4_restrictionsongatherings |   .0055724   .0162828     0.34   0.732    -.0263726    .0375174
  Yc6_stayathomerequirements |  -.0118385   .0210069    -0.56   0.573    -.0530516    .0293746
        Yc2_workplaceclosing |  -.0098853   .0153839    -0.64   0.521    -.0400666     .020296
                       _cons |    .582312   .0597587     9.74   0.000     .4650726    .6995515
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        60           1          59     |
         pid |      4871        4871           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. estimates store fes

. 
. coefplot (fes, label(With Individual FEs) xline(2 3, lwidth(.5in) lc(gray*.2)) mcolor(blue) ciopts(lcolor(blue)) ///
> keep(   dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dmonthdum19     dmont
> hdum20) ///
> yline(0, lcolor(black) lwidth(thin) lpattern(dash))) ///
> (nofes, label (Without Individual FEs) mcolor( eltblue) ciopts(lcolor( eltblue)) ///
> keep(   dmonthdum13     dmonthdum14     dmonthdum15     dmonthdum16     dmonthdum17     dmonthdum18     dmonthdum19     dmont
> hdum20)), vertical ///
> coeflabels ( dmonthdum12="1/21" dmonthdum13="2/21" dmonthdum14="3/21" dmonthdum15="4/21" dmonthdum16="5/21" dmonthdum17="6/21
> " dmonthdum18="7/21" dmonthdum19="8/21" dmonthdum20="9/21")  xlabel(, angle(45)) ///
> legend(position(6) rows(1)) ///
> plotregion(color(white)) graphregion(color(white))   ///
> saving("Vac_under65.gph", replace) ///
> title("Vaccination status: Age<65 (base month Jan 2021)") xtitle("Pandemic Month")
(file Vac_under65.gph not found)
file Vac_under65.gph saved

. 
. * Save plot
. grc1leg Vac_under65.gph Vac_65_plus.gph ///
> , imargin(2 2 2 2) row(2) col(2) legendfrom(Vac_under65.gph) iscale(*.75) plotregion(color(white)) graphregion(color(white)) 
>  

. graph export "figures\Figure S19.png", replace width(2200) height(1100)
file figures\Figure S19.png saved as PNG format

. 
. * Delete the intermediate files
. erase Vac_under65.gph 

. erase Vac_65_plus.gph

. 
. 
. *****************
. *** Table S20 ***
. *****************
. 
. *Alternative Analyses for Table 1, Ever-Treated as Control Group
. 
. clear

. use "data_gallup.dta"

. 
. // Create ever_vaccinated variable
. bysort pid: egen ever_vac=max(vaccinated)
(24 missing values generated)

. 
. // Key variables
. gen vac_dem=vaccinated*dem
(9,310 missing values generated)

. gen vac_ind=vaccinated*indep_third
(9,310 missing values generated)

. gen vac_gop=vaccinated*gop
(9,310 missing values generated)

. 
. label variable vac_dem "Vaccinated x Democrat"

. label variable vac_ind "Vaccinated x Independent"

. 
. *TWFE, ever-treated as control
. reghdfe Mostly_Isol vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restric
> tionsongatherings Yc6_stayathomerequirements  if ever_vac==1  [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 2060 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     48,925
Absorbing 2 HDFE groups                           F(  11,  11775) =       5.31
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5754
                                                  Adj R-squared   =     0.4365
                                                  Within R-sq.    =     0.0044
Number of clusters (pid)     =     11,776         Root MSE        =     0.3753

                                               (Std. err. adjusted for 11,776 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |   -.043875   .0149257    -2.94   0.003    -.0731319   -.0146181
                     vac_ind |  -.0096957   .0168955    -0.57   0.566    -.0428138    .0234223
                  vaccinated |  -.0095089   .0166061    -0.57   0.567    -.0420596    .0230418
                         dem |    .006077   .0258071     0.24   0.814    -.0445092    .0566633
                 indep_third |  -.0066715   .0217828    -0.31   0.759    -.0493694    .0360263
        ZLNpc_new_cases_7day |   .0160324   .0055871     2.87   0.004     .0050808    .0269841
               out_workforce |   .0035286   .0332287     0.11   0.915    -.0616051    .0686624
                    employed |   -.109729   .0274242    -4.00   0.000     -.163485   -.0559729
                      income |  -.0045989   .0052866    -0.87   0.384    -.0149616    .0057638
Yc4_restrictionsongatherings |  -.0023723   .0136434    -0.17   0.862    -.0291156    .0243711
  Yc6_stayathomerequirements |   .0030783   .0116241     0.26   0.791    -.0197068    .0258634
                       _cons |    .605074   .0449383    13.46   0.000     .5169875    .6931605
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     11776       11776           0    *|
        time |       275           1         274     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S20 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated) replace 
tables\Table S20 TOP PANEL.xls
dir : seeout

. reghdfe worn_mask vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restricti
> onsongatherings Yc6_stayathomerequirements  if ever_vac==1  [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 2197 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     43,490
Absorbing 2 HDFE groups                           F(  11,  11600) =      20.33
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5302
                                                  Adj R-squared   =     0.3539
                                                  Within R-sq.    =     0.0182
Number of clusters (pid)     =     11,601         Root MSE        =     0.2677

                                               (Std. err. adjusted for 11,601 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                   worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |   .1698996   .0143215    11.86   0.000      .141827    .1979722
                     vac_ind |   .1108997   .0166659     6.65   0.000     .0782317    .1435678
                  vaccinated |  -.1382179   .0155681    -8.88   0.000    -.1687339   -.1077018
                         dem |  -.0665728   .0237904    -2.80   0.005    -.1132061   -.0199396
                 indep_third |  -.0443749   .0225333    -1.97   0.049     -.088544   -.0002059
        ZLNpc_new_cases_7day |   .0337577   .0045494     7.42   0.000     .0248401    .0426753
               out_workforce |   -.006374   .0264296    -0.24   0.809    -.0581806    .0454325
                    employed |   .0011054   .0196927     0.06   0.955    -.0374956    .0397065
                      income |  -.0115176   .0045555    -2.53   0.011    -.0204472   -.0025881
Yc4_restrictionsongatherings |   -.001679   .0104653    -0.16   0.873    -.0221928    .0188348
  Yc6_stayathomerequirements |    .023514   .0088886     2.65   0.008     .0060908    .0409371
                       _cons |   .9783836   .0372975    26.23   0.000     .9052742    1.051493
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     11601       11601           0    *|
        time |       257           1         256     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S20 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated)
tables\Table S20 TOP PANEL.xls
dir : seeout

. reghdfe v_worry_ill vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restric
> tionsongatherings Yc6_stayathomerequirements  if ever_vac==1  [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 2262 singleton observations)
(MWFE estimator converged in 12 iterations)

HDFE Linear regression                            Number of obs   =     42,354
Absorbing 2 HDFE groups                           F(  11,  11528) =      13.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6039
                                                  Adj R-squared   =     0.4511
                                                  Within R-sq.    =     0.0105
Number of clusters (pid)     =     11,529         Root MSE        =     0.2319

                                               (Std. err. adjusted for 11,529 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0875695   .0088934    -9.85   0.000    -.1050021   -.0701369
                     vac_ind |  -.0252428   .0097358    -2.59   0.010    -.0443266   -.0061589
                  vaccinated |  -.0043674   .0096286    -0.45   0.650     -.023241    .0145063
                         dem |   .0345643   .0154532     2.24   0.025     .0042733    .0648553
                 indep_third |  -.0010222   .0109301    -0.09   0.925    -.0224471    .0204027
        ZLNpc_new_cases_7day |   .0147441   .0039735     3.71   0.000     .0069555    .0225328
               out_workforce |  -.0760618   .0238445    -3.19   0.001    -.1228011   -.0293225
                    employed |   -.054332   .0195506    -2.78   0.005    -.0926545   -.0160095
                      income |   .0021745   .0038919     0.56   0.576    -.0054543    .0098033
Yc4_restrictionsongatherings |  -.0080974   .0089075    -0.91   0.363    -.0255575    .0093627
  Yc6_stayathomerequirements |  -.0005179   .0078802    -0.07   0.948    -.0159644    .0149286
                       _cons |   .1564174   .0323131     4.84   0.000     .0930782    .2197566
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     11529       11529           0    *|
        time |       253           1         252     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S20 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated)
tables\Table S20 TOP PANEL.xls
dir : seeout

. reghdfe mostly_remote vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day income Yc4_restrictionsongatherings Yc6
> _stayathomerequirements  if ever_vac==1 & employed==1 [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 1978 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =     19,591
Absorbing 2 HDFE groups                           F(   9,   6018) =       2.82
Statistics robust to heteroskedasticity           Prob > F        =     0.0026
                                                  R-squared       =     0.7945
                                                  Adj R-squared   =     0.6981
                                                  Within R-sq.    =     0.0034
Number of clusters (pid)     =      6,019         Root MSE        =     0.2738

                                                (Std. err. adjusted for 6,019 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0723486   .0192746    -3.75   0.000    -.1101336   -.0345635
                     vac_ind |  -.0565299    .019675    -2.87   0.004    -.0950998   -.0179599
                  vaccinated |   .0153035   .0189639     0.81   0.420    -.0218726    .0524796
                         dem |   .0331023   .0307072     1.08   0.281    -.0270949    .0932995
                 indep_third |   .0135198   .0249121     0.54   0.587    -.0353169    .0623565
        ZLNpc_new_cases_7day |  -.0049007   .0076128    -0.64   0.520    -.0198244     .010023
                      income |   .0050309   .0064134     0.78   0.433    -.0075416    .0176034
Yc4_restrictionsongatherings |   .0107982   .0147936     0.73   0.465    -.0182026     .039799
  Yc6_stayathomerequirements |   .0125876   .0129405     0.97   0.331    -.0127804    .0379556
                       _cons |   .4077393   .0503757     8.09   0.000      .308985    .5064936
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |      6019        6019           0    *|
        time |       228           1         227     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S20 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated)
tables\Table S20 TOP PANEL.xls
dir : seeout

. 
. clear

. use "stacked_did_data_ever_treated.dta"

. 
. gen _cohort_unit = st_unit

. gen _cohort_time = st_time

. gen _cohort = Cohort

. 
. label variable dem_vac "Vaccinated x Democrat"

. label variable ind_vac "Vaccinated x Independent"

. label variable vaccinated "Vaccinated"

. 
. *Estimate Stacked DID, ever-treated as control group
. stackdid Mostly_Isol dem_vac ind_vac vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restri
> ctionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  vce(cl _cohort_unit) nobuild tr(vaccinated) group(_cohort_unit) 
(dropped 59092 singleton observations)
(MWFE estimator converged in 20 iterations)

HDFE Linear regression                            Number of obs   =  1,075,677
Absorbing 2 HDFE groups                           F(  11, 323365) =      37.25
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6105
                                                  Adj R-squared   =     0.4320
                                                  Within R-sq.    =     0.0017
Number of clusters (_cohort_unit) =    323,366    Root MSE        =     0.3723

                                     (Std. err. adjusted for 323,366 clusters in _cohort_unit)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     dem_vac |  -.0391387   .0147691    -2.65   0.008    -.0680856   -.0101917
                     ind_vac |  -.0110144   .0160552    -0.69   0.493    -.0424822    .0204533
                  vaccinated |  -.0484747   .0149107    -3.25   0.001    -.0776993   -.0192502
                         dem |   .0002484   .0056757     0.04   0.965    -.0108758    .0113725
                 indep_third |   .0017311   .0047869     0.36   0.718     -.007651    .0111133
        ZLNpc_new_cases_7day |   .0011008   .0012775     0.86   0.389    -.0014032    .0036047
               out_workforce |  -.0040058   .0075825    -0.53   0.597    -.0188673    .0108557
                    employed |  -.0896209    .006131   -14.62   0.000    -.1016375   -.0776043
                      income |  -.0015132   .0012787    -1.18   0.237    -.0040195     .000993
Yc4_restrictionsongatherings |  -.0055206   .0034365    -1.61   0.108    -.0122561    .0012149
  Yc6_stayathomerequirements |   .0016137   .0024045     0.67   0.502     -.003099    .0063264
                       _cons |   .6461066   .0106247    60.81   0.000     .6252824    .6669308
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
 _cohort_time |     14713           1       14712     |
 _cohort_unit |    323366      323366           0    *|
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S20 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(dem_vac ind_vac vaccinated) replace 
tables\Table S20 LOWER PANEL.xls
dir : seeout

. stackdid worn_mask dem_vac ind_vac vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restrict
> ionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  vce(cl _cohort_unit) nobuild tr(vaccinated) group(_cohort_unit) 
(dropped 73056 singleton observations)
(MWFE estimator converged in 21 iterations)

HDFE Linear regression                            Number of obs   =    885,083
Absorbing 2 HDFE groups                           F(  11, 301868) =     225.74
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6137
                                                  Adj R-squared   =     0.3997
                                                  Within R-sq.    =     0.0134
Number of clusters (_cohort_unit) =    301,869    Root MSE        =     0.2539

                                     (Std. err. adjusted for 301,869 clusters in _cohort_unit)
----------------------------------------------------------------------------------------------
                             |               Robust
                   worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     dem_vac |   .1593952   .0134019    11.89   0.000     .1331278    .1856626
                     ind_vac |   .0961856   .0155159     6.20   0.000     .0657748    .1265964
                  vaccinated |  -.1481308   .0143184   -10.35   0.000    -.1761945   -.1200672
                         dem |  -.0197567   .0048044    -4.11   0.000    -.0291731   -.0103403
                 indep_third |   .0006248   .0044059     0.14   0.887    -.0080107    .0092602
        ZLNpc_new_cases_7day |   .0360195   .0010556    34.12   0.000     .0339506    .0380884
               out_workforce |  -.0816563   .0068674   -11.89   0.000    -.0951162   -.0681964
                    employed |  -.0382313   .0047334    -8.08   0.000    -.0475087    -.028954
                      income |  -.0170496   .0010944   -15.58   0.000    -.0191946   -.0149046
Yc4_restrictionsongatherings |  -.0155475   .0029004    -5.36   0.000    -.0212322   -.0098628
  Yc6_stayathomerequirements |   .0389402   .0019074    20.42   0.000     .0352018    .0426786
                       _cons |   1.032181   .0088702   116.36   0.000     1.014796    1.049567
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
 _cohort_time |     13669           1       13668     |
 _cohort_unit |    301869      301869           0    *|
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S20 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(dem_vac ind_vac vaccinated)
tables\Table S20 LOWER PANEL.xls
dir : seeout

. stackdid v_worry_ill dem_vac ind_vac vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restri
> ctionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  vce(cl _cohort_unit) nobuild tr(vaccinated) group(_cohort_unit) 
(dropped 81321 singleton observations)
(MWFE estimator converged in 21 iterations)

HDFE Linear regression                            Number of obs   =    841,414
Absorbing 2 HDFE groups                           F(  11, 291103) =      74.95
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6956
                                                  Adj R-squared   =     0.5229
                                                  Within R-sq.    =     0.0043
Number of clusters (_cohort_unit) =    291,104    Root MSE        =     0.2310

                                     (Std. err. adjusted for 291,104 clusters in _cohort_unit)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     dem_vac |  -.0852267   .0086811    -9.82   0.000    -.1022415    -.068212
                     ind_vac |  -.0247792   .0088956    -2.79   0.005    -.0422143   -.0073441
                  vaccinated |  -.0131243    .008581    -1.53   0.126    -.0299428    .0036943
                         dem |    .003606   .0038438     0.94   0.348    -.0039278    .0111397
                 indep_third |  -.0122467   .0026637    -4.60   0.000    -.0174675    -.007026
        ZLNpc_new_cases_7day |   .0114475   .0008837    12.95   0.000     .0097156    .0131795
               out_workforce |  -.1035842   .0055055   -18.81   0.000    -.1143747   -.0927936
                    employed |  -.0802639   .0041882   -19.16   0.000    -.0884727   -.0720552
                      income |  -.0025345   .0009542    -2.66   0.008    -.0044048   -.0006643
Yc4_restrictionsongatherings |  -.0170602   .0024734    -6.90   0.000    -.0219079   -.0122124
  Yc6_stayathomerequirements |   .0039298   .0016705     2.35   0.019     .0006557    .0072039
                       _cons |   .2417505   .0078904    30.64   0.000     .2262856    .2572154
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
 _cohort_time |     13413           1       13412     |
 _cohort_unit |    291104      291104           0    *|
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S20 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(dem_vac ind_vac vaccinated)
tables\Table S20 LOWER PANEL.xls
dir : seeout

. stackdid mostly_remote dem_vac ind_vac vaccinated dem indep_third ZLNpc_new_cases_7day income Yc4_restrictionsongatherings Yc
> 6_stayathomerequirements if employed==1 [aw=WEIGHT],  vce(cl _cohort_unit) nobuild tr(vaccinated) group(_cohort_unit) 
(dropped 78510 singleton observations)
(MWFE estimator converged in 28 iterations)

HDFE Linear regression                            Number of obs   =    346,996
Absorbing 2 HDFE groups                           F(   9, 128398) =      22.94
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8499
                                                  Adj R-squared   =     0.7481
                                                  Within R-sq.    =     0.0027
Number of clusters (_cohort_unit) =    128,399    Root MSE        =     0.2509

                                     (Std. err. adjusted for 128,399 clusters in _cohort_unit)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     dem_vac |  -.0646251   .0184886    -3.50   0.000    -.1008624   -.0283877
                     ind_vac |  -.0459362   .0185889    -2.47   0.013    -.0823702   -.0095022
                  vaccinated |  -.0050359   .0185214    -0.27   0.786    -.0413375    .0312657
                         dem |   .0154024    .007662     2.01   0.044     .0003851    .0304197
                 indep_third |  -.0090449    .005787    -1.56   0.118    -.0203873    .0022975
        ZLNpc_new_cases_7day |  -.0180022   .0019242    -9.36   0.000    -.0217736   -.0142307
                      income |   .0128016   .0016338     7.84   0.000     .0095994    .0160038
Yc4_restrictionsongatherings |   .0034307   .0043416     0.79   0.429    -.0050787    .0119401
  Yc6_stayathomerequirements |   .0124123   .0027614     4.49   0.000     .0069999    .0178246
                       _cons |   .4155196   .0132657    31.32   0.000     .3895191    .4415202
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
------------------------------------------------------+
  Absorbed FE | Categories  - Redundant  = Num. Coefs |
--------------+---------------------------------------|
 _cohort_time |     11758           1       11757     |
 _cohort_unit |    128399      128399           0    *|
------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S20 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(dem_vac ind_vac vaccinated)
tables\Table S20 LOWER PANEL.xls
dir : seeout

. 
. 
. ******************
. *** Figure S21 ***
. ******************
. 
. * Pre-trend Responses, Ever Vaccinated versus Never Vaccinated
. * See R script Figures_made_in_R.R 
. 
. 
. *****************
. *** Table S22 ***
. *****************
. 
. *Alternative TWFE Analysis of Pre- versus Post- Vaccination Status
. 
. clear

. use "data_gallup.dta"

. 
. // Create ever_vaccinated variable
. bysort pid: egen ever_vac=max(vaccinated)
(24 missing values generated)

. 
. // Key variables
. gen vac_dem=vaccinated*dem
(9,310 missing values generated)

. gen vac_ind=vaccinated*indep_third
(9,310 missing values generated)

. gen vac_gop=vaccinated*gop
(9,310 missing values generated)

. 
. * Sort the data by pid and time
. sort pid time 

. by pid: gen lag_v1 = vaccinated[_n-1]
(54,312 missing values generated)

. by pid: gen lead_v1 = vaccinated[_n+1]
(54,448 missing values generated)

. 
. label variable lag_v1 "Lag vaccinated"

. label variable lead_v1 "Lead vaccinated"

. label variable vac_dem "Vaccinated x Democrat"

. label variable vac_ind "Vaccinated x Independent"

. 
. * Top Panel: Two-way fixed effects, including never-treated
. reghdfe Mostly_Isol vac_dem vac_ind vaccinated lag_v1 lead_v1 dem indep_third  ZLNpc_new_cases_7day out_workforce employed in
> come Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 12158 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =     48,934
Absorbing 2 HDFE groups                           F(  13,  17493) =       5.61
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6438
                                                  Adj R-squared   =     0.4409
                                                  Within R-sq.    =     0.0061
Number of clusters (pid)     =     17,494         Root MSE        =     0.3732

                                               (Std. err. adjusted for 17,494 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |   -.055329   .0256746    -2.16   0.031    -.1056538   -.0050043
                     vac_ind |  -.0064985   .0293818    -0.22   0.825    -.0640897    .0510928
                  vaccinated |  -.0416626   .0212007    -1.97   0.049    -.0832181    -.000107
                      lag_v1 |  -.0905914    .022279    -4.07   0.000    -.1342603   -.0469224
                     lead_v1 |  -.0094578   .0108394    -0.87   0.383    -.0307041    .0117885
                         dem |  -.0132251   .0286607    -0.46   0.644    -.0694029    .0429527
                 indep_third |  -.0001504   .0191118    -0.01   0.994    -.0376114    .0373105
        ZLNpc_new_cases_7day |   .0193681   .0061334     3.16   0.002      .007346    .0313901
               out_workforce |   .0356961   .0377534     0.95   0.344    -.0383044    .1096965
                    employed |  -.0703285   .0302741    -2.32   0.020    -.1296687   -.0109883
                      income |  -.0031191   .0062406    -0.50   0.617    -.0153512     .009113
Yc4_restrictionsongatherings |  -.0074679   .0144008    -0.52   0.604    -.0356949    .0207591
  Yc6_stayathomerequirements |  -.0085992   .0124084    -0.69   0.488    -.0329209    .0157225
                       _cons |   .5370052   .0494119    10.87   0.000     .4401531    .6338574
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     17494       17494           0    *|
        time |       249           1         248     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S22 TOP PANEL.xls", excel adjr2 lab dec(3) replace keep(vac_dem vac_ind vaccinated lag_v1 lead_v1
> )
tables\Table S22 TOP PANEL.xls
dir : seeout

. reghdfe worn_mask vac_dem vac_ind vaccinated lag_v1 lead_v1 dem indep_third   ZLNpc_new_cases_7day out_workforce employed inc
> ome Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 12162 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =     48,985
Absorbing 2 HDFE groups                           F(  13,  17506) =       8.85
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6677
                                                  Adj R-squared   =     0.4786
                                                  Within R-sq.    =     0.0110
Number of clusters (pid)     =     17,507         Root MSE        =     0.2746

                                               (Std. err. adjusted for 17,507 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                   worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |   .1313689   .0218039     6.03   0.000     .0886311    .1741067
                     vac_ind |   .1273794   .0265707     4.79   0.000     .0752982    .1794605
                  vaccinated |  -.0979791   .0210487    -4.65   0.000    -.1392366   -.0567216
                      lag_v1 |  -.0070399    .019161    -0.37   0.713    -.0445975    .0305176
                     lead_v1 |  -.0079515   .0070304    -1.13   0.258    -.0217317    .0058288
                         dem |  -.0394472   .0220178    -1.79   0.073    -.0826043    .0037098
                 indep_third |  -.0361724   .0196745    -1.84   0.066    -.0747364    .0023915
        ZLNpc_new_cases_7day |   .0356626   .0047223     7.55   0.000     .0264066    .0449187
               out_workforce |  -.0280988    .031183    -0.90   0.368    -.0892205    .0330229
                    employed |   .0048541   .0208362     0.23   0.816    -.0359871    .0456952
                      income |  -.0092417   .0049322    -1.87   0.061    -.0189093     .000426
Yc4_restrictionsongatherings |  -.0214036   .0120655    -1.77   0.076    -.0450531     .002246
  Yc6_stayathomerequirements |   .0175836   .0087181     2.02   0.044     .0004952     .034672
                       _cons |   .9194799   .0406047    22.64   0.000     .8398906    .9990691
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     17507       17507           0    *|
        time |       249           1         248     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S22 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated lag_v1 lead_v1)
tables\Table S22 TOP PANEL.xls
dir : seeout

. reghdfe v_worry_ill vac_dem vac_ind vaccinated lag_v1 lead_v1 dem indep_third   ZLNpc_new_cases_7day out_workforce employed i
> ncome Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 12188 singleton observations)
(MWFE estimator converged in 14 iterations)

HDFE Linear regression                            Number of obs   =     48,291
Absorbing 2 HDFE groups                           F(  13,  17288) =       9.11
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6680
                                                  Adj R-squared   =     0.4784
                                                  Within R-sq.    =     0.0104
Number of clusters (pid)     =     17,289         Root MSE        =     0.2207

                                               (Std. err. adjusted for 17,289 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0954557   .0141025    -6.77   0.000    -.1230981   -.0678134
                     vac_ind |   -.016204   .0152661    -1.06   0.289    -.0461271     .013719
                  vaccinated |  -.0176869   .0107856    -1.64   0.101    -.0388277    .0034538
                      lag_v1 |  -.0176834   .0131438    -1.35   0.179    -.0434467    .0080798
                     lead_v1 |  -.0001903   .0067804    -0.03   0.978    -.0134807       .0131
                         dem |   .0333164   .0169287     1.97   0.049     .0001345    .0664984
                 indep_third |  -.0085082   .0080352    -1.06   0.290     -.024258    .0072415
        ZLNpc_new_cases_7day |   .0099707   .0034869     2.86   0.004      .003136    .0168055
               out_workforce |  -.0858968   .0267317    -3.21   0.001    -.1382937      -.0335
                    employed |  -.0749842   .0219743    -3.41   0.001    -.1180561   -.0319123
                      income |  -.0050221   .0042658    -1.18   0.239    -.0133834    .0033393
Yc4_restrictionsongatherings |  -.0095882   .0087748    -1.09   0.275    -.0267878    .0076114
  Yc6_stayathomerequirements |   .0057583   .0068936     0.84   0.404    -.0077539    .0192705
                       _cons |   .2085243   .0354103     5.89   0.000     .1391166     .277932
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     17289       17289           0    *|
        time |       248           1         247     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S22 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated lag_v1 lead_v1)
tables\Table S22 TOP PANEL.xls
dir : seeout

. reghdfe mostly_remote vac_dem vac_ind vaccinated lag_v1 lead_v1 dem indep_third   ZLNpc_new_cases_7day income Yc4_restriction
> songatherings Yc6_stayathomerequirements if employed==1 [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 6924 singleton observations)
(MWFE estimator converged in 16 iterations)

HDFE Linear regression                            Number of obs   =     19,204
Absorbing 2 HDFE groups                           F(  11,   7070) =       2.09
Statistics robust to heteroskedasticity           Prob > F        =     0.0176
                                                  R-squared       =     0.8255
                                                  Adj R-squared   =     0.7184
                                                  Within R-sq.    =     0.0039
Number of clusters (pid)     =      7,071         Root MSE        =     0.2636

                                                (Std. err. adjusted for 7,071 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0423202   .0353798    -1.20   0.232    -.1116752    .0270347
                     vac_ind |  -.0176435   .0367488    -0.48   0.631    -.0896822    .0543953
                  vaccinated |  -.0305233   .0314709    -0.97   0.332    -.0922157     .031169
                      lag_v1 |   .0097062   .0240714     0.40   0.687    -.0374809    .0568933
                     lead_v1 |  -.0202575   .0116315    -1.74   0.082    -.0430587    .0025437
                         dem |  -.0227942   .0310277    -0.73   0.463    -.0836177    .0380293
                 indep_third |  -.0264515   .0203079    -1.30   0.193     -.066261    .0133581
        ZLNpc_new_cases_7day |  -.0063455   .0076933    -0.82   0.410    -.0214267    .0087358
                      income |   -.004526   .0066236    -0.68   0.494    -.0175103    .0084583
Yc4_restrictionsongatherings |  -.0209861   .0171493    -1.22   0.221     -.054604    .0126317
  Yc6_stayathomerequirements |   .0086801   .0122536     0.71   0.479    -.0153406    .0327009
                       _cons |   .5158679   .0475492    10.85   0.000     .4226572    .6090786
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |      7071        7071           0    *|
        time |       226           1         225     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S22 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated lag_v1 lead_v1)
tables\Table S22 TOP PANEL.xls
dir : seeout

. 
. *Brandice: mostly_remote is off
. 
. * Lower Panel: Two-way fixed effects, excluding never-treated
. reghdfe Mostly_Isol vac_dem vac_ind vaccinated lag_v1 lead_v1 dem indep_third ZLNpc_new_cases_7day out_workforce employed inc
> ome Yc4_restrictionsongatherings Yc6_stayathomerequirements [aw=WEIGHT] if ever_vac==1,  a(pid time) vce(cl pid)
(dropped 2264 singleton observations)
(MWFE estimator converged in 17 iterations)

HDFE Linear regression                            Number of obs   =     25,796
Absorbing 2 HDFE groups                           F(  13,   8240) =       2.59
Statistics robust to heteroskedasticity           Prob > F        =     0.0014
                                                  R-squared       =     0.6192
                                                  Adj R-squared   =     0.4323
                                                  Within R-sq.    =     0.0047
Number of clusters (pid)     =      8,241         Root MSE        =     0.3766

                                                (Std. err. adjusted for 8,241 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0630244   .0258614    -2.44   0.015    -.1137192   -.0123295
                     vac_ind |  -.0103422   .0298245    -0.35   0.729    -.0688056    .0481212
                  vaccinated |  -.0151358   .0247883    -0.61   0.541    -.0637272    .0334556
                      lag_v1 |  -.0739689   .0247696    -2.99   0.003    -.1225236   -.0254141
                     lead_v1 |  -.0036964   .0131888    -0.28   0.779    -.0295498    .0221569
                         dem |    .036812   .0348783     1.06   0.291    -.0315583    .1051822
                 indep_third |   .0345725   .0274194     1.26   0.207    -.0191763    .0883214
        ZLNpc_new_cases_7day |   .0163572   .0082884     1.97   0.048     .0001099    .0326046
               out_workforce |   .0205024   .0491882     0.42   0.677    -.0759188    .1169237
                    employed |  -.0821764   .0389294    -2.11   0.035    -.1584879   -.0058649
                      income |   .0004533   .0078373     0.06   0.954    -.0149098    .0158164
Yc4_restrictionsongatherings |  -.0124527   .0187352    -0.66   0.506    -.0491784    .0242729
  Yc6_stayathomerequirements |  -.0170886   .0155204    -1.10   0.271    -.0475125    .0133353
                       _cons |   .5455468   .0642471     8.49   0.000     .4196063    .6714874
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |      8241        8241           0    *|
        time |       240           1         239     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S22 LOWER PANEL.xls", excel adjr2 lab dec(3) replace keep(vac_dem vac_ind vaccinated lag_v1 lead_
> v1)
tables\Table S22 LOWER PANEL.xls
dir : seeout

. reghdfe worn_mask vac_dem vac_ind vaccinated lag_v1 lead_v1 dem indep_third ZLNpc_new_cases_7day out_workforce employed incom
> e Yc4_restrictionsongatherings Yc6_stayathomerequirements if ever_vac==1 [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 2259 singleton observations)
(MWFE estimator converged in 17 iterations)

HDFE Linear regression                            Number of obs   =     25,833
Absorbing 2 HDFE groups                           F(  13,   8248) =       6.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5518
                                                  Adj R-squared   =     0.3321
                                                  Within R-sq.    =     0.0139
Number of clusters (pid)     =      8,249         Root MSE        =     0.2418

                                                (Std. err. adjusted for 8,249 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                   worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |   .1261736   .0217889     5.79   0.000     .0834619    .1688853
                     vac_ind |   .1148268   .0265066     4.33   0.000     .0628671    .1667864
                  vaccinated |  -.1139373   .0230703    -4.94   0.000     -.159161   -.0687137
                      lag_v1 |  -.0261994   .0207211    -1.26   0.206    -.0668181    .0144192
                     lead_v1 |  -.0105124   .0082554    -1.27   0.203     -.026695    .0056701
                         dem |  -.0149265   .0286315    -0.52   0.602    -.0710514    .0411985
                 indep_third |  -.0085268   .0277257    -0.31   0.758    -.0628762    .0458225
        ZLNpc_new_cases_7day |   .0327675   .0054081     6.06   0.000     .0221662    .0433688
               out_workforce |  -.0356473   .0357081    -1.00   0.318    -.1056441    .0343496
                    employed |  -.0041588   .0217952    -0.19   0.849     -.046883    .0385653
                      income |  -.0117858   .0060407    -1.95   0.051     -.023627    .0000554
Yc4_restrictionsongatherings |  -.0118312   .0132939    -0.89   0.374    -.0378905    .0142282
  Yc6_stayathomerequirements |    .023599   .0099938     2.36   0.018     .0040086    .0431893
                       _cons |   .9996581   .0472021    21.18   0.000     .9071301    1.092186
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |      8249        8249           0    *|
        time |       240           1         239     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S22 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated lag_v1 lead_v1)
tables\Table S22 LOWER PANEL.xls
dir : seeout

. reghdfe v_worry_ill vac_dem vac_ind vaccinated lag_v1 lead_v1 dem indep_third  ZLNpc_new_cases_7day out_workforce employed in
> come Yc4_restrictionsongatherings Yc6_stayathomerequirements if ever_vac [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 2290 singleton observations)
(MWFE estimator converged in 17 iterations)

HDFE Linear regression                            Number of obs   =     25,579
Absorbing 2 HDFE groups                           F(  13,   8204) =       6.78
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6515
                                                  Adj R-squared   =     0.4794
                                                  Within R-sq.    =     0.0113
Number of clusters (pid)     =      8,205         Root MSE        =     0.2345

                                                (Std. err. adjusted for 8,205 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0921962   .0144728    -6.37   0.000    -.1205665   -.0638259
                     vac_ind |  -.0124567   .0159802    -0.78   0.436    -.0437819    .0188686
                  vaccinated |  -.0046609   .0141746    -0.33   0.742    -.0324466    .0231248
                      lag_v1 |  -.0103362   .0148805    -0.69   0.487    -.0395058    .0188333
                     lead_v1 |  -.0040659   .0084928    -0.48   0.632    -.0207139    .0125821
                         dem |   .0204706   .0211477     0.97   0.333    -.0209843    .0619255
                 indep_third |  -.0140179   .0128209    -1.09   0.274    -.0391502    .0111144
        ZLNpc_new_cases_7day |    .013159   .0049118     2.68   0.007     .0035307    .0227874
               out_workforce |  -.1330691   .0319287    -4.17   0.000    -.1956573   -.0704808
                    employed |  -.1028008   .0248313    -4.14   0.000    -.1514765   -.0541251
                      income |   -.002652   .0055245    -0.48   0.631    -.0134814    .0081773
Yc4_restrictionsongatherings |  -.0258071   .0124654    -2.07   0.038    -.0502424   -.0013718
  Yc6_stayathomerequirements |   .0069361   .0093898     0.74   0.460    -.0114702    .0253425
                       _cons |   .2639061   .0446788     5.91   0.000     .1763243     .351488
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |      8205        8205           0    *|
        time |       239           1         238     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S22 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated lag_v1 lead_v1)
tables\Table S22 LOWER PANEL.xls
dir : seeout

. reghdfe mostly_remote vac_dem vac_ind vaccinated lag_v1 lead_v1 dem indep_third ZLNpc_new_cases_7day income Yc4_restrictionso
> ngatherings Yc6_stayathomerequirements if employed==1 & ever_vac==1 [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 1957 singleton observations)
(MWFE estimator converged in 16 iterations)

HDFE Linear regression                            Number of obs   =     10,995
Absorbing 2 HDFE groups                           F(  11,   3776) =       1.10
Statistics robust to heteroskedasticity           Prob > F        =     0.3555
                                                  R-squared       =     0.8238
                                                  Adj R-squared   =     0.7231
                                                  Within R-sq.    =     0.0030
Number of clusters (pid)     =      3,777         Root MSE        =     0.2629

                                                (Std. err. adjusted for 3,777 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0382659   .0358169    -1.07   0.285    -.1084883    .0319565
                     vac_ind |  -.0145016   .0368948    -0.39   0.694    -.0868372     .057834
                  vaccinated |  -.0288205   .0331266    -0.87   0.384    -.0937683    .0361273
                      lag_v1 |   .0054295    .026795     0.20   0.839    -.0471045    .0579636
                     lead_v1 |  -.0126157   .0138266    -0.91   0.362    -.0397241    .0144926
                         dem |   .0041378    .037784     0.11   0.913    -.0699412    .0782168
                 indep_third |  -.0166621   .0280719    -0.59   0.553    -.0716998    .0383755
        ZLNpc_new_cases_7day |  -.0105651   .0102233    -1.03   0.301    -.0306088    .0094786
                      income |  -.0031385   .0083798    -0.37   0.708    -.0195679    .0132909
Yc4_restrictionsongatherings |  -.0129765   .0211539    -0.61   0.540    -.0544507    .0284976
  Yc6_stayathomerequirements |   .0107832   .0152663     0.71   0.480    -.0191477    .0407141
                       _cons |   .5286978   .0648276     8.16   0.000     .4015973    .6557983
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |      3777        3777           0    *|
        time |       213           1         212     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S22 LOWER PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated lag_v1 lead_v1)
tables\Table S22 LOWER PANEL.xls
dir : seeout

. 
. 
. *****************
. *** Table S23 ***
. *****************
. 
. * Alternative TWFE Difference-in-differences, Party Identification 
. 
. clear

. use "data_gallup.dta"

. 
. // Create ever_vaccinated variable
. bysort pid: egen ever_vac=max(vaccinated)
(24 missing values generated)

. 
. // Key variables
. gen vac_dem=vaccinated*dem
(9,310 missing values generated)

. gen vac_ind=vaccinated*indep_third
(9,310 missing values generated)

. gen vac_gop=vaccinated*gop
(9,310 missing values generated)

. 
. egen minparty=min(party), by(pid)
(816 missing values generated)

. egen maxparty=max(party), by(pid)
(816 missing values generated)

. gen switchparty=1 if minparty!=maxparty
(135,609 missing values generated)

. replace switchparty=0 if minparty==maxparty
(135,609 real changes made)

. 
. sort pid time

. iis pid

. tis time

. by pid: gen firstinpanel=1 if _n==1
(110,111 missing values generated)

. by pid: replace firstinpanel=0 if _n!=1
(110111 real changes made)

. 
. gen firstdem=1 if firstinpanel==1 & dem==1
(145,081 missing values generated)

. replace firstdem=0 if firstinpanel==1 & dem==0
(26,709 real changes made)

. bysort pid (firstdem): replace firstdem= firstdem[1]
(86999 real changes made)

. 
. gen firstindep=1 if firstinpanel==1 & indep==1
(154,341 missing values generated)

. replace firstindep=0 if firstinpanel==1 & indep==0
(35,969 real changes made)

. bysort pid (firstindep): replace firstindep= firstindep[1]
(86999 real changes made)

. 
. gen firstgop=1 if firstinpanel==1 & gop==1
(148,842 missing values generated)

. replace firstgop=0 if firstinpanel==1 & gop==0
(30,470 real changes made)

. bysort pid (firstgop): replace firstgop= firstgop[1]
(86999 real changes made)

. 
. label variable vac_dem "Vaccinated x Democrat"

. label variable vac_ind "Vaccinated x Independent"

. 
. *Estimate TWFE model without party switchers
. reghdfe Mostly_Isol vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restric
> tionsongatherings Yc6_stayathomerequirements if switchparty==0 [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 12429 singleton observations)
(MWFE estimator converged in 12 iterations)
note: dem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: indep_third is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =    104,114
Absorbing 2 HDFE groups                           F(   9,  31250) =      13.03
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6091
                                                  Adj R-squared   =     0.4393
                                                  Within R-sq.    =     0.0049
Number of clusters (pid)     =     31,251         Root MSE        =     0.3744

                                               (Std. err. adjusted for 31,251 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0433212     .01604    -2.70   0.007    -.0747601   -.0118822
                     vac_ind |  -.0110344    .019632    -0.56   0.574     -.049514    .0274452
                  vaccinated |  -.0592236   .0146658    -4.04   0.000     -.087969   -.0304781
                         dem |          0  (omitted)
                 indep_third |          0  (omitted)
        ZLNpc_new_cases_7day |    .014889   .0044646     3.33   0.001     .0061382    .0236398
               out_workforce |  -.0228842   .0279307    -0.82   0.413    -.0776295     .031861
                    employed |  -.1018218   .0222909    -4.57   0.000    -.1455128   -.0581309
                      income |   -.003014   .0045583    -0.66   0.508    -.0119485    .0059205
Yc4_restrictionsongatherings |  -.0112858   .0107925    -1.05   0.296    -.0324395    .0098679
  Yc6_stayathomerequirements |   .0108256     .00932     1.16   0.245     -.007442    .0290933
                       _cons |   .6053228   .0345394    17.53   0.000     .5376242    .6730214
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     31251       31251           0    *|
        time |       284           1         283     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S23 TOP PANEL.xls", excel adjr2 lab dec(3) replace keep(vac_dem vac_ind vaccinated)
tables\Table S23 TOP PANEL.xls
dir : seeout

. reghdfe worn_mask vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restricti
> onsongatherings Yc6_stayathomerequirements if switchparty==0 [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 13425 singleton observations)
(MWFE estimator converged in 12 iterations)
note: dem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: indep_third is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     86,214
Absorbing 2 HDFE groups                           F(   9,  28531) =      25.51
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6394
                                                  Adj R-squared   =     0.4585
                                                  Within R-sq.    =     0.0129
Number of clusters (pid)     =     28,532         Root MSE        =     0.2857

                                               (Std. err. adjusted for 28,532 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                   worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |   .1678969   .0157132    10.69   0.000     .1370983    .1986956
                     vac_ind |   .1171529    .019678     5.95   0.000     .0785831    .1557227
                  vaccinated |  -.1111413     .01602    -6.94   0.000    -.1425412   -.0797415
                         dem |          0  (omitted)
                 indep_third |          0  (omitted)
        ZLNpc_new_cases_7day |   .0381481   .0038388     9.94   0.000      .030624    .0456723
               out_workforce |   .0053786   .0247545     0.22   0.828    -.0431415    .0538986
                    employed |    .015716   .0183759     0.86   0.392    -.0203016    .0517337
                      income |   -.007753   .0037623    -2.06   0.039    -.0151274   -.0003787
Yc4_restrictionsongatherings |  -.0037697   .0096821    -0.39   0.697     -.022747    .0152077
  Yc6_stayathomerequirements |    .012244   .0074355     1.65   0.100      -.00233    .0268179
                       _cons |   .8378686   .0297612    28.15   0.000     .7795352     .896202
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     28532       28532           0    *|
        time |       266           1         265     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S23 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated)
tables\Table S23 TOP PANEL.xls
dir : seeout

. reghdfe v_worry_ill vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day out_workforce employed income Yc4_restric
> tionsongatherings Yc6_stayathomerequirements if switchparty==0 [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 13894 singleton observations)
(MWFE estimator converged in 12 iterations)
note: dem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: indep_third is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     82,120
Absorbing 2 HDFE groups                           F(   9,  27476) =      22.35
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6492
                                                  Adj R-squared   =     0.4701
                                                  Within R-sq.    =     0.0109
Number of clusters (pid)     =     27,477         Root MSE        =     0.2246

                                               (Std. err. adjusted for 27,477 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |  -.0954688   .0096369    -9.91   0.000    -.1143575     -.07658
                     vac_ind |    -.03434    .011423    -3.01   0.003    -.0567297   -.0119502
                  vaccinated |  -.0151689   .0075484    -2.01   0.044     -.029964   -.0003737
                         dem |          0  (omitted)
                 indep_third |          0  (omitted)
        ZLNpc_new_cases_7day |    .008565   .0029449     2.91   0.004     .0027928    .0143371
               out_workforce |  -.0746124   .0206758    -3.61   0.000     -.115138   -.0340868
                    employed |  -.0441892   .0180761    -2.44   0.015    -.0796192   -.0087591
                      income |  -.0018357   .0032746    -0.56   0.575     -.008254    .0045827
Yc4_restrictionsongatherings |   .0039689   .0069166     0.57   0.566     -.009588    .0175258
  Yc6_stayathomerequirements |   -.001714    .006251    -0.27   0.784    -.0139663    .0105383
                       _cons |   .1761533   .0275498     6.39   0.000     .1221542    .2301524
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     27477       27477           0    *|
        time |       262           1         261     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S23 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated)
tables\Table S23 TOP PANEL.xls
dir : seeout

. reghdfe mostly_remote vac_dem vac_ind vaccinated dem indep_third ZLNpc_new_cases_7day income Yc4_restrictionsongatherings Yc6
> _stayathomerequirements  [aw=WEIGHT] if employed==1 & switchparty==0,  a(pid time) vce(cl pid)
(dropped 9887 singleton observations)
(MWFE estimator converged in 13 iterations)
note: dem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: indep_third is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     33,847
Absorbing 2 HDFE groups                           F(   7,  12026) =       4.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8118
                                                  Adj R-squared   =     0.7047
                                                  Within R-sq.    =     0.0036
Number of clusters (pid)     =     12,027         Root MSE        =     0.2704

                                               (Std. err. adjusted for 12,027 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                     vac_dem |   -.079385   .0207195    -3.83   0.000    -.1199985   -.0387715
                     vac_ind |   -.058505   .0224807    -2.60   0.009    -.1025709   -.0144391
                  vaccinated |   .0077159   .0191438     0.40   0.687     -.029809    .0452409
                         dem |          0  (omitted)
                 indep_third |          0  (omitted)
        ZLNpc_new_cases_7day |   .0017509   .0060212     0.29   0.771    -.0100517    .0135535
                      income |   .0012422   .0053704     0.23   0.817    -.0092847    .0117692
Yc4_restrictionsongatherings |  -.0069053   .0128784    -0.54   0.592     -.032149    .0183384
  Yc6_stayathomerequirements |   .0058969   .0102386     0.58   0.565    -.0141724    .0259662
                       _cons |   .4547354   .0360217    12.62   0.000     .3841272    .5253437
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     12027       12027           0    *|
        time |       242           1         241     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S23 TOP PANEL.xls", excel adjr2 lab dec(3) keep(vac_dem vac_ind vaccinated)
tables\Table S23 TOP PANEL.xls
dir : seeout

. 
. *Estimate TWFE model based on first party
. gen vac_firstdem=vaccinated*firstdem
(31,599 missing values generated)

. gen vac_firstindep=vaccinated*firstindep
(31,599 missing values generated)

. 
. label variable vac_firstdem "Vaccinated x Democrat"

. label variable vac_firstindep "Vaccinated x Independent"

. 
. reghdfe Mostly_Isol vac_firstdem vac_firstind vaccinated firstdem firstindep ZLNpc_new_cases_7day out_workforce employed inco
> me Yc4_restrictionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 11567 singleton observations)
(MWFE estimator converged in 13 iterations)
note: firstdem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: firstindep is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =    109,413
Absorbing 2 HDFE groups                           F(   9,  31855) =      17.49
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6041
                                                  Adj R-squared   =     0.4394
                                                  Within R-sq.    =     0.0065
Number of clusters (pid)     =     31,856         Root MSE        =     0.3744

                                               (Std. err. adjusted for 31,856 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 Mostly_Isol | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                vac_firstdem |   -.043297   .0155701    -2.78   0.005     -.073815   -.0127789
              vac_firstindep |  -.0307649   .0182918    -1.68   0.093    -.0666176    .0050878
                  vaccinated |  -.0564275    .013666    -4.13   0.000    -.0832133   -.0296417
                    firstdem |          0  (omitted)
                  firstindep |          0  (omitted)
        ZLNpc_new_cases_7day |   .0222894      .0043     5.18   0.000     .0138613    .0307176
               out_workforce |  -.0305233   .0254798    -1.20   0.231    -.0804646     .019418
                    employed |  -.1225424   .0207968    -5.89   0.000     -.163305   -.0817799
                      income |  -.0053294   .0041416    -1.29   0.198     -.013447    .0027883
Yc4_restrictionsongatherings |   -.006467   .0103758    -0.62   0.533     -.026804    .0138699
  Yc6_stayathomerequirements |   .0050112    .008918     0.56   0.574    -.0124685    .0224908
                       _cons |   .6270973   .0316217    19.83   0.000     .5651177     .689077
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     31856       31856           0    *|
        time |       284           1         283     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S23 LOWER PANEL.xls", excel adjr2 lab dec(3) replace keep(vac_firstdem vac_firstind vaccinated)
tables\Table S23 LOWER PANEL.xls
dir : seeout

. reghdfe worn_mask vac_firstdem vac_firstind vaccinated firstdem firstindep ZLNpc_new_cases_7day out_workforce employed income
>  Yc4_restrictionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 12870 singleton observations)
(MWFE estimator converged in 13 iterations)
note: firstdem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: firstindep is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     87,747
Absorbing 2 HDFE groups                           F(   9,  28793) =      27.77
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6422
                                                  Adj R-squared   =     0.4649
                                                  Within R-sq.    =     0.0123
Number of clusters (pid)     =     28,794         Root MSE        =     0.2891

                                               (Std. err. adjusted for 28,794 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                   worn_mask | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                vac_firstdem |   .1503859   .0142488    10.55   0.000     .1224575    .1783142
              vac_firstindep |    .092538    .017798     5.20   0.000     .0576531    .1274229
                  vaccinated |  -.0636213   .0142034    -4.48   0.000    -.0914606    -.035782
                    firstdem |          0  (omitted)
                  firstindep |          0  (omitted)
        ZLNpc_new_cases_7day |   .0354335   .0037863     9.36   0.000     .0280122    .0428548
               out_workforce |   .0066319   .0230167     0.29   0.773    -.0384819    .0517456
                    employed |   .0183633     .01762     1.04   0.297    -.0161728    .0528993
                      income |  -.0106145    .003691    -2.88   0.004     -.017849     -.00338
Yc4_restrictionsongatherings |  -.0061465   .0090688    -0.68   0.498    -.0239218    .0116289
  Yc6_stayathomerequirements |   .0206764   .0075332     2.74   0.006     .0059109    .0354419
                       _cons |   .8403459   .0282096    29.79   0.000     .7850537    .8956381
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     28794       28794           0    *|
        time |       266           1         265     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S23 LOWER PANEL.xls", excel adjr2 lab dec(3)  keep(vac_firstdem vac_firstind vaccinated)
tables\Table S23 LOWER PANEL.xls
dir : seeout

. reghdfe v_worry_ill vac_firstdem vac_firstind vaccinated firstdem firstindep ZLNpc_new_cases_7day out_workforce employed inco
> me Yc4_restrictionsongatherings Yc6_stayathomerequirements  [aw=WEIGHT],  a(pid time) vce(cl pid)
(dropped 13344 singleton observations)
(MWFE estimator converged in 13 iterations)
note: firstdem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: firstindep is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     83,714
Absorbing 2 HDFE groups                           F(   9,  27778) =      20.16
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6396
                                                  Adj R-squared   =     0.4580
                                                  Within R-sq.    =     0.0091
Number of clusters (pid)     =     27,779         Root MSE        =     0.2199

                                               (Std. err. adjusted for 27,779 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
                 v_worry_ill | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                vac_firstdem |  -.0821827   .0095857    -8.57   0.000    -.1009712   -.0633943
              vac_firstindep |  -.0357505   .0120753    -2.96   0.003    -.0594186   -.0120824
                  vaccinated |  -.0150455   .0074833    -2.01   0.044     -.029713   -.0003779
                    firstdem |          0  (omitted)
                  firstindep |          0  (omitted)
        ZLNpc_new_cases_7day |   .0117729   .0028323     4.16   0.000     .0062214    .0173244
               out_workforce |  -.0544749   .0188742    -2.89   0.004    -.0914692   -.0174806
                    employed |  -.0340931   .0162318    -2.10   0.036    -.0659081   -.0022781
                      income |  -.0000663   .0028033    -0.02   0.981    -.0055609    .0054284
Yc4_restrictionsongatherings |  -.0001659   .0069756    -0.02   0.981    -.0138384    .0135066
  Yc6_stayathomerequirements |   .0032241   .0058896     0.55   0.584    -.0083197    .0147679
                       _cons |      .1442   .0238129     6.06   0.000     .0975255    .1908744
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     27779       27779           0    *|
        time |       262           1         261     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S23 LOWER PANEL.xls", excel adjr2 lab dec(3)  keep(vac_firstdem vac_firstind vaccinated)
tables\Table S23 LOWER PANEL.xls
dir : seeout

. reghdfe mostly_remote vac_firstdem vac_firstind vaccinated firstdem firstindep ZLNpc_new_cases_7day income Yc4_restrictionson
> gatherings Yc6_stayathomerequirements  [aw=WEIGHT] if employed==1 ,  a(pid time) vce(cl pid)
(dropped 9552 singleton observations)
(MWFE estimator converged in 13 iterations)
note: firstdem is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
note: firstindep is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)

HDFE Linear regression                            Number of obs   =     35,742
Absorbing 2 HDFE groups                           F(   7,  12541) =       3.90
Statistics robust to heteroskedasticity           Prob > F        =     0.0003
                                                  R-squared       =     0.8061
                                                  Adj R-squared   =     0.6980
                                                  Within R-sq.    =     0.0025
Number of clusters (pid)     =     12,542         Root MSE        =     0.2725

                                               (Std. err. adjusted for 12,542 clusters in pid)
----------------------------------------------------------------------------------------------
                             |               Robust
               mostly_remote | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                vac_firstdem |  -.0498046    .019256    -2.59   0.010    -.0875493   -.0120598
              vac_firstindep |  -.0588763   .0218809    -2.69   0.007    -.1017662   -.0159863
                  vaccinated |  -.0050765   .0174083    -0.29   0.771    -.0391994    .0290465
                    firstdem |          0  (omitted)
                  firstindep |          0  (omitted)
        ZLNpc_new_cases_7day |   .0003581   .0058654     0.06   0.951    -.0111389     .011855
                      income |   .0054516   .0049591     1.10   0.272     -.004269    .0151722
Yc4_restrictionsongatherings |  -.0032842   .0120899    -0.27   0.786    -.0269823    .0204138
  Yc6_stayathomerequirements |    .003128   .0101675     0.31   0.758    -.0168018    .0230578
                       _cons |   .4098442   .0335816    12.20   0.000     .3440191    .4756694
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
         pid |     12542       12542           0    *|
        time |       243           1         242     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S23 LOWER PANEL.xls", excel adjr2 lab dec(3)  keep(vac_firstdem vac_firstind vaccinated)
tables\Table S23 LOWER PANEL.xls
dir : seeout

. 
. 
. ******************
. *** Figure S24 ***
. ******************
. 
. *Map of Gatherings Restrictions and Stay-at-Home Orders 
. * See R script Figures_made_in_R.R 
. 
. ******************
. *** Figure S25 ***
. ******************
. 
. *Nominal versus Effective Samples for Table 2
. * See R script Figures_made_in_R.R 
. 
. *****************
. *** Table S26 ***
. *****************
. 
. *Control Variable Estimates for Table 2 
. 
. clear

. use "data_gallup.dta"

. 
. label variable LNpc_new_cases_7day "Log per capita COVID-19 cases (county)"

. label variable out_workforce "Out of workforce"

. label variable AmerInd "American Indian or Native Hawaiian"

. label variable age10 "Age"

. label variable age_group4 "Age 65 and up (indicator)"

. label variable somecol "Some college"

. label variable income "Income"

. 
. 
. *GOP governors only
. reghdfe approvestate dem indep ZLNpc_new_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 
> age_group4 somecol ba grad live_w_children income if gopgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 5 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 2 HDFE groups                           F(  18,     25) =      79.47
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1598
                                                  Adj R-squared   =     0.1481
                                                  Within R-sq.    =     0.1110
Number of clusters (stateid) =         26         Root MSE        =     0.4074

                                       (Std. err. adjusted for 26 clusters in stateid)
--------------------------------------------------------------------------------------
                     |               Robust
approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 dem |  -.2531698   .0554162    -4.57   0.000    -.3673017    -.139038
               indep |  -.1306318   .0574867    -2.27   0.032    -.2490279   -.0122357
ZLNpc_new_cases_7day |  -.0472893   .0167367    -2.83   0.009    -.0817592   -.0128195
            employed |    .133976   .0973648     1.38   0.181    -.0665504    .3345025
       out_workforce |   .1485348   .0939087     1.58   0.126    -.0448737    .3419434
                male |  -.0197117   .0217709    -0.91   0.374    -.0645498    .0251263
               Black |   .1168445   .0392253     2.98   0.006     .0360586    .1976305
                Hisp |    .044835    .027211     1.65   0.112     -.011207    .1008771
               Asian |   .3558646   .1354491     2.63   0.014      .076902    .6348272
             AmerInd |  -.2619356   .1456019    -1.80   0.084    -.5618084    .0379372
         Multiracial |  -.0368332   .1088146    -0.34   0.738    -.2609411    .1872747
               age10 |   .0419045   .0077149     5.43   0.000     .0260154    .0577935
          age_group4 |  -.0715401   .0308087    -2.32   0.029    -.1349917   -.0080884
             somecol |   .0021903   .0325374     0.07   0.947    -.0648217    .0692024
                  ba |   .0119962   .0446496     0.27   0.790    -.0799613    .1039538
                grad |  -.0311455   .0410463    -0.76   0.455    -.1156818    .0533909
     live_w_children |  -.0753312   .0184211    -4.09   0.000    -.1132701   -.0373923
              income |  -.0078088   .0068486    -1.14   0.265    -.0219138    .0062962
               _cons |   .5290586   .1013123     5.22   0.000     .3204021    .7377152
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        26          26           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S26.xls", excel adjr2 lab dec(3) replace keep(ZLNpc_new_cases_7day employed out_workforce male  B
> lack Hisp Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_children income)
tables\Table S26.xls
dir : seeout

. 
. reghdfe approvestate  dem indep demrestrictionsongatherings Yc4_restrictionsongatherings indrestrictionsongatherings  ZLNpc_n
> ew_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_chil
> dren income ///
> if gopgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 2 HDFE groups                           F(  21,     25) =      67.99
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1665
                                                  Adj R-squared   =     0.1543
                                                  Within R-sq.    =     0.1181
Number of clusters (stateid) =         26         Root MSE        =     0.4059

                                               (Std. err. adjusted for 26 clusters in stateid)
----------------------------------------------------------------------------------------------
                             |               Robust
        approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   -.417561   .0629865    -6.63   0.000    -.5472841    -.287838
                       indep |  -.1121865   .0456398    -2.46   0.021    -.2061835   -.0181894
 demrestrictionsongatherings |   .1943836   .0797051     2.44   0.022     .0302279    .3585393
Yc4_restrictionsongatherings |  -.0476928     .07493    -0.64   0.530    -.2020139    .1066284
 indrestrictionsongatherings |  -.0269719    .075024    -0.36   0.722    -.1814867    .1275429
        ZLNpc_new_cases_7day |  -.0506705   .0167378    -3.03   0.006    -.0851426   -.0161984
                    employed |   .1229603   .1002248     1.23   0.231    -.0834566    .3293771
               out_workforce |   .1387839   .0953464     1.46   0.158    -.0575857    .3351536
                        male |  -.0229429   .0216356    -1.06   0.299    -.0675023    .0216164
                       Black |    .131036   .0411223     3.19   0.004     .0463431     .215729
                        Hisp |   .0434244   .0273435     1.59   0.125    -.0128906    .0997394
                       Asian |   .3614791   .1322453     2.73   0.011     .0891149    .6338433
                     AmerInd |  -.2652346   .1488177    -1.78   0.087    -.5717303    .0412611
                 Multiracial |  -.0415318   .1092195    -0.38   0.707    -.2664736      .18341
                       age10 |   .0431543   .0074725     5.78   0.000     .0277643    .0585442
                  age_group4 |  -.0724554   .0297807    -2.43   0.022      -.13379   -.0111208
                     somecol |   .0044732   .0323814     0.14   0.891    -.0622175    .0711639
                          ba |   .0127077   .0454275     0.28   0.782    -.0808519    .1062674
                        grad |  -.0281932   .0412325    -0.68   0.500    -.1131131    .0567266
             live_w_children |  -.0716748   .0193269    -3.71   0.001    -.1114793   -.0318704
                      income |  -.0076868   .0068194    -1.13   0.270    -.0217317    .0063581
                       _cons |   .5645088   .1033816     5.46   0.000     .3515904    .7774272
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        26          26           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S26.xls", excel adjr2 lab dec(3) keep(ZLNpc_new_cases_7day employed out_workforce male  Black His
> p Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_children income)
tables\Table S26.xls
dir : seeout

. 
. reghdfe approvestate  dem indep demstay Yc6_stayathome indstay ZLNpc_new_cases_7day employed out_workforce male  Black Hisp A
> sian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_children income ///
> if gopgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 2 HDFE groups                           F(  21,     25) =     112.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1625
                                                  Adj R-squared   =     0.1501
                                                  Within R-sq.    =     0.1138
Number of clusters (stateid) =         26         Root MSE        =     0.4069

                                             (Std. err. adjusted for 26 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       dem |  -.2073401   .0708529    -2.93   0.007    -.3532643   -.0614159
                     indep |  -.1013123   .0523986    -1.93   0.065    -.2092293    .0066047
 demstayathomerequirements |  -.0898998   .0764697    -1.18   0.251    -.2473921    .0675926
Yc6_stayathomerequirements |  -.0051538    .071111    -0.07   0.943    -.1516097    .1413021
 indstayathomerequirements |  -.0601355   .0893644    -0.67   0.507     -.244185     .123914
      ZLNpc_new_cases_7day |  -.0459324   .0172946    -2.66   0.014    -.0815513   -.0103136
                  employed |   .1330595   .0907577     1.47   0.155    -.0538595    .3199784
             out_workforce |   .1530036    .089972     1.70   0.101    -.0322973    .3383046
                      male |  -.0198799   .0220995    -0.90   0.377    -.0653946    .0256348
                     Black |   .1193279   .0391265     3.05   0.005     .0387454    .1999104
                      Hisp |   .0497785   .0288111     1.73   0.096    -.0095591    .1091161
                     Asian |    .362882   .1328548     2.73   0.011     .0892624    .6365015
                   AmerInd |  -.2650258   .1604642    -1.65   0.111    -.5955081    .0654565
               Multiracial |  -.0447153   .1065506    -0.42   0.678    -.2641604    .1747298
                     age10 |   .0412355   .0076257     5.41   0.000     .0255301    .0569409
                age_group4 |  -.0734843   .0307011    -2.39   0.025    -.1367144   -.0102541
                   somecol |   .0003876   .0320484     0.01   0.990    -.0656172    .0663924
                        ba |   .0099467   .0443334     0.22   0.824    -.0813596    .1012529
                      grad |  -.0308632   .0404838    -0.76   0.453     -.114241    .0525147
           live_w_children |  -.0733086   .0185042    -3.96   0.001    -.1114187   -.0351984
                    income |  -.0073098   .0070433    -1.04   0.309    -.0218158    .0071962
                     _cons |   .5330345   .0938217     5.68   0.000     .3398052    .7262639
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        26          26           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S26.xls", excel adjr2 lab dec(3) keep(ZLNpc_new_cases_7day employed out_workforce male  Black His
> p Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_children income)
tables\Table S26.xls
dir : seeout

. 
. *DEM governors only
. reghdfe approvestate gop indep ZLNpc_new_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 
> age_group4 somecol ba grad live_w_children income  if demgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  18,     23) =      47.46
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1313
                                                  Adj R-squared   =     0.1226
                                                  Within R-sq.    =     0.0887
Number of clusters (stateid) =         24         Root MSE        =     0.3873

                                       (Std. err. adjusted for 24 clusters in stateid)
--------------------------------------------------------------------------------------
                     |               Robust
approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------+----------------------------------------------------------------
                 gop |  -.1977938   .0371345    -5.33   0.000    -.2746124   -.1209752
               indep |   -.117616   .0235349    -5.00   0.000    -.1663016   -.0689304
ZLNpc_new_cases_7day |   .0272277   .0143945     1.89   0.071    -.0025496     .057005
            employed |  -.0030539   .0427447    -0.07   0.944     -.091478    .0853701
       out_workforce |   .0366947   .0549307     0.67   0.511    -.0769381    .1503275
                male |  -.0678072   .0226303    -3.00   0.006    -.1146214   -.0209929
               Black |   -.009394   .0483581    -0.19   0.848    -.1094304    .0906424
                Hisp |    .043986   .0351794     1.25   0.224    -.0287882    .1167603
               Asian |   .1523258   .0310748     4.90   0.000     .0880426    .2166089
             AmerInd |   .1122449    .066694     1.68   0.106    -.0257221    .2502119
         Multiracial |  -.0397241   .0620222    -0.64   0.528    -.1680268    .0885785
               age10 |   .0254344   .0130264     1.95   0.063    -.0015128    .0523816
          age_group4 |   .0024981   .0571362     0.04   0.966    -.1156973    .1206934
             somecol |   .0419282   .0360724     1.16   0.257    -.0326932    .1165496
                  ba |   .0424452   .0285495     1.49   0.151    -.0166139    .1015044
                grad |   .1160485   .0340444     3.41   0.002     .0456224    .1864746
     live_w_children |  -.0053796   .0193051    -0.28   0.783    -.0453152     .034556
              income |    .001612   .0059532     0.27   0.789    -.0107032    .0139273
               _cons |   .7275114   .0830357     8.76   0.000     .5557389    .8992839
--------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S26.xls", excel adjr2 lab dec(3) keep(ZLNpc_new_cases_7day employed out_workforce male  Black His
> p Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_children income)
tables\Table S26.xls
dir : seeout

. 
. reghdfe approvestate  gop indep goprestrictionsongatherings indrestrictionsongatherings Yc4_restrictionsongatherings  ///
> ZLNpc_new_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live
> _w_children income ///
> if demgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  21,     23) =     676.26
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1347
                                                  Adj R-squared   =     0.1255
                                                  Within R-sq.    =     0.0922
Number of clusters (stateid) =         24         Root MSE        =     0.3866

                                               (Std. err. adjusted for 24 clusters in stateid)
----------------------------------------------------------------------------------------------
                             |               Robust
        approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         gop |  -.2504735   .0096364   -25.99   0.000    -.2704079   -.2305391
                       indep |  -.2713828   .0629804    -4.31   0.000    -.4016677    -.141098
 goprestrictionsongatherings |   .0568972   .0380374     1.50   0.148    -.0217892    .1355835
 indrestrictionsongatherings |   .1618585   .0703871     2.30   0.031     .0162517    .3074653
Yc4_restrictionsongatherings |    .055757   .0244211     2.28   0.032     .0052381    .1062759
        ZLNpc_new_cases_7day |   .0250736   .0138767     1.81   0.084    -.0036325    .0537798
                    employed |  -.0049236   .0438541    -0.11   0.912    -.0956427    .0857955
               out_workforce |   .0343352   .0552484     0.62   0.540    -.0799549    .1486253
                        male |  -.0685589   .0228077    -3.01   0.006    -.1157403   -.0213776
                       Black |   -.008888   .0487088    -0.18   0.857    -.1096499    .0918739
                        Hisp |   .0443175   .0353934     1.25   0.223    -.0288993    .1175342
                       Asian |   .1528843   .0286719     5.33   0.000     .0935719    .2121966
                     AmerInd |    .114795   .0681612     1.68   0.106    -.0262072    .2557971
                 Multiracial |   -.045748   .0628651    -0.73   0.474    -.1757944    .0842984
                       age10 |   .0267015   .0129484     2.06   0.051    -.0000844    .0534873
                  age_group4 |  -.0012187   .0545818    -0.02   0.982    -.1141298    .1116924
                     somecol |   .0411207   .0356744     1.15   0.261    -.0326775    .1149189
                          ba |   .0445821   .0275143     1.62   0.119    -.0123355    .1014997
                        grad |   .1155468   .0334385     3.46   0.002      .046374    .1847196
             live_w_children |  -.0049084   .0192091    -0.26   0.801    -.0446454    .0348286
                      income |   .0010629   .0060307     0.18   0.862    -.0114126    .0135384
                       _cons |   .6739512    .079216     8.51   0.000     .5100804    .8378221
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S26.xls", excel adjr2 lab dec(3) keep(ZLNpc_new_cases_7day employed out_workforce male  Black His
> p Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_children income)
tables\Table S26.xls
dir : seeout

. 
. reghdfe approvestate  gop indep  gopstay indstay Yc6_stayathome ///
> ZLNpc_new_cases_7day employed out_workforce male  Black Hisp Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live
> _w_children income ///
> if demgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  21,     23) =      60.47
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1355
                                                  Adj R-squared   =     0.1263
                                                  Within R-sq.    =     0.0930
Number of clusters (stateid) =         24         Root MSE        =     0.3865

                                             (Std. err. adjusted for 24 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       gop |  -.1390802    .047646    -2.92   0.008    -.2376434   -.0405169
                     indep |  -.1195252   .0470359    -2.54   0.018    -.2168265   -.0222239
 gopstayathomerequirements |  -.1064382   .0540183    -1.97   0.061    -.2181836    .0053071
 indstayathomerequirements |    .003251   .0653042     0.05   0.961     -.131841     .138343
Yc6_stayathomerequirements |  -.0183116   .0398619    -0.46   0.650    -.1007722    .0641489
      ZLNpc_new_cases_7day |   .0290106    .014699     1.97   0.061    -.0013966    .0594177
                  employed |  -.0074478   .0444142    -0.17   0.868    -.0993256    .0844301
             out_workforce |    .032457   .0556331     0.58   0.565    -.0826289    .1475428
                      male |  -.0694535   .0218586    -3.18   0.004    -.1146714   -.0242356
                     Black |  -.0096012   .0487331    -0.20   0.846    -.1104133    .0912109
                      Hisp |   .0424424   .0352852     1.20   0.241    -.0305506    .1154355
                     Asian |   .1564022   .0301186     5.19   0.000     .0940972    .2187073
                   AmerInd |   .1115334   .0665665     1.68   0.107      -.02617    .2492367
               Multiracial |  -.0365188   .0619789    -0.59   0.561    -.1647318    .0916943
                     age10 |   .0244538   .0130684     1.87   0.074    -.0025803    .0514878
                age_group4 |   .0016005   .0583612     0.03   0.978    -.1191289      .12233
                   somecol |   .0389615   .0360308     1.08   0.291    -.0355738    .1134968
                        ba |   .0375941   .0288849     1.30   0.206    -.0221589    .0973472
                      grad |   .1107935   .0329032     3.37   0.003      .042728     .178859
           live_w_children |  -.0080212   .0189041    -0.42   0.675    -.0471273    .0310849
                    income |   .0020545   .0057929     0.35   0.726    -.0099289     .014038
                     _cons |   .7505903   .0927022     8.10   0.000     .5588212    .9423594
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S26.xls", excel adjr2 lab dec(3) keep(ZLNpc_new_cases_7day employed out_workforce male  Black His
> p Asian AmerInd  Multiracial age10 age_group4 somecol ba grad live_w_children income)
tables\Table S26.xls
dir : seeout

. 
. 
. ******************
. *** Figure S27 ***
. ******************
. 
. * Marginal Predictions for Table 2
. 
. clear

. use "data_gallup.dta"

. 
. gen party_recode=party
(9,064 missing values generated)

. recode party_recode (3=1) (1=3)
(113,992 changes made to party_recode)

. 
. label define prec 3 "Dem." 2 "Indep." 1 "Repub." , replace

. label values party_recode prec

. 
. *Columns 3 and 4
. reghdfe approvestate  party_recode##Yc4_restrictionsongatherings  ZLNpc_new_cases_7day out_workforce employed male age10 age_
> group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live_w_children income ///
> if gopgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 2 HDFE groups                           F(  21,     25) =      61.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1769
                                                  Adj R-squared   =     0.1648
                                                  Within R-sq.    =     0.1291
Number of clusters (stateid) =         26         Root MSE        =     0.4034

                                                            (Std. err. adjusted for 26 clusters in stateid)
-----------------------------------------------------------------------------------------------------------
                                          |               Robust
                     approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
------------------------------------------+----------------------------------------------------------------
                             party_recode |
                                  Indep.  |  -.0739217   .0435735    -1.70   0.102     -.163663    .0158197
                                    Dem.  |  -.4086879   .0660666    -6.19   0.000    -.5447546   -.2726213
                                          |
           1.Yc4_restrictionsongatherings |  -.0026516   .0778767    -0.03   0.973    -.1630417    .1577384
                                          |
party_recode#Yc4_restrictionsongatherings |
                                Indep.#1  |  -.1243217   .0669415    -1.86   0.075    -.2621902    .0135469
                                  Dem.#1  |   .1455056   .0806755     1.80   0.083    -.0206487      .31166
                                          |
                     ZLNpc_new_cases_7day |  -.0517485   .0166135    -3.11   0.005    -.0859647   -.0175323
                            out_workforce |   .1268671   .0950855     1.33   0.194    -.0689652    .3226995
                                 employed |   .1135335   .0989473     1.15   0.262    -.0902523    .3173193
                                     male |  -.0264315   .0221808    -1.19   0.245    -.0721138    .0192508
                                    age10 |   .0388578   .0081979     4.74   0.000     .0219739    .0557416
                               age_group4 |  -.0620126   .0282377    -2.20   0.038    -.1201692    -.003856
                                  somecol |   .0054269   .0321306     0.17   0.867    -.0607473    .0716011
                                       ba |   .0111295   .0452034     0.25   0.808    -.0819687    .1042276
                                     grad |  -.0302865   .0400704    -0.76   0.457     -.112813      .05224
                                  AmerInd |  -.2664877   .1462109    -1.82   0.080    -.5676146    .0346393
                                    Asian |   .3666286   .1295773     2.83   0.009     .0997591    .6334981
                                    Black |   .1400026   .0399031     3.51   0.002     .0578206    .2221846
                                     Hisp |   .0474391   .0284513     1.67   0.108    -.0111575    .1060357
                              Multiracial |  -.0381857   .1094212    -0.35   0.730    -.2635428    .1871715
                          live_w_children |  -.0625789   .0198728    -3.15   0.004    -.1035076   -.0216502
                                   income |   -.009359   .0067503    -1.39   0.178    -.0232615    .0045435
                                    _cons |   .5923235   .1087294     5.45   0.000     .3683911    .8162559
-----------------------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        26          26           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. margins party_recode##Yc4_restrictionsongatherings

Predictive margins                                       Number of obs = 4,002
Model VCE: Robust

Expression: Linear prediction, predict()

-----------------------------------------------------------------------------------------------------------
                                          |            Delta-method
                                          |     Margin   std. err.      z    P>|z|     [95% conf. interval]
------------------------------------------+----------------------------------------------------------------
                             party_recode |
                                  Repub.  |   .8908313   .0329473    27.04   0.000     .8262557    .9554069
                                  Indep.  |   .7177526   .0236867    30.30   0.000     .6713275    .7641776
                                    Dem.  |   .5981965   .0225122    26.57   0.000     .5540734    .6423195
                                          |
             Yc4_restrictionsongatherings |
                                       0  |   .7205149   .0372101    19.36   0.000     .6475846    .7934453
                                       1  |   .7349527   .0098296    74.77   0.000     .7156871    .7542183
                                          |
party_recode#Yc4_restrictionsongatherings |
                                Repub.#0  |   .8929462   .0616708    14.48   0.000     .7720736    1.013819
                                Repub.#1  |   .8902946   .0402915    22.10   0.000     .8113247    .9692644
                                Indep.#0  |   .8190246   .0440875    18.58   0.000     .7326147    .9054344
                                Indep.#1  |   .6920512   .0283302    24.43   0.000     .6365251    .7475774
                                  Dem.#0  |   .4842583   .0406179    11.92   0.000     .4046486     .563868
                                  Dem.#1  |   .6271123   .0273683    22.91   0.000     .5734713    .6807533
-----------------------------------------------------------------------------------------------------------

. marginsplot

Variables that uniquely identify margins: party_recode Yc4_restrictionsongatherings

. marginsplot, saving(app1, replace)  ///
> ci1opts(lc(green) lp(dash))  plot1opts(lc(green) connect(none) mc(green) mlcolor(green) msymbol(Dh)) ///
> ci2opts(lc(blue) lp(dash))  plot2opts(lc(blue) connect(none) mc(blue) mlcolor(blue) msymbol(Oh)) ///
> xtitle("") title("Predicted approval of Republican governor" "by whether restrictions on gatherings are in effect") plot3opts
> (lc(none) mc(none)) ci3opts(col(none)) leg(pos(6) order(1 "Not in effect" 2 "In effect" 3 "") rows(1) rowgap(*1.5) colgap(*1.
> 5) )

Variables that uniquely identify margins: party_recode Yc4_restrictionsongatherings
(file app1.gph not found)
file app1.gph saved

. 
. 
. reghdfe approvestate  party_recode##Yc6_stayathome ZLNpc_new_cases_7day out_workforce employed male age10 age_group4   someco
> l ba grad AmerInd Asian Black Hisp Multiracial live_w_children income ///
> if gopgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 2 HDFE groups                           F(  21,     25) =     145.92
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1710
                                                  Adj R-squared   =     0.1588
                                                  Within R-sq.    =     0.1229
Number of clusters (stateid) =         26         Root MSE        =     0.4048

                                                          (Std. err. adjusted for 26 clusters in stateid)
---------------------------------------------------------------------------------------------------------
                                        |               Robust
                   approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------------------+----------------------------------------------------------------
                           party_recode |
                                Indep.  |  -.1425295   .0435409    -3.27   0.003    -.2322037   -.0528553
                                  Dem.  |  -.2378793   .0663369    -3.59   0.001    -.3745028   -.1012558
                                        |
           1.Yc6_stayathomerequirements |  -.0103454   .0752011    -0.14   0.892    -.1652249    .1445341
                                        |
party_recode#Yc6_stayathomerequirements |
                              Indep.#1  |  -.0561545   .0907022    -0.62   0.541    -.2429593    .1306502
                                Dem.#1  |  -.0872382   .0692344    -1.26   0.219    -.2298292    .0553527
                                        |
                   ZLNpc_new_cases_7day |  -.0472005   .0171791    -2.75   0.011    -.0825815   -.0118195
                          out_workforce |   .1411467   .0901298     1.57   0.130    -.0444792    .3267725
                               employed |   .1234159   .0906399     1.36   0.185    -.0632605    .3100922
                                   male |  -.0209363   .0222908    -0.94   0.357    -.0668451    .0249724
                                  age10 |   .0371502   .0081013     4.59   0.000     .0204654    .0538351
                             age_group4 |  -.0656775   .0293695    -2.24   0.034    -.1261651   -.0051899
                                somecol |     .00046    .031804     0.01   0.989    -.0650417    .0659616
                                     ba |   .0063032    .043742     0.14   0.887    -.0837852    .0963916
                                   grad |  -.0328123   .0393154    -0.83   0.412    -.1137839    .0481593
                                AmerInd |  -.2644148   .1585371    -1.67   0.108    -.5909282    .0620985
                                  Asian |   .3623094   .1314561     2.76   0.011     .0915704    .6330483
                                  Black |   .1289262   .0388691     3.32   0.003     .0488738    .2089786
                                   Hisp |   .0540656   .0285713     1.89   0.070    -.0047781    .1129093
                            Multiracial |  -.0396348   .1073275    -0.37   0.715      -.26068    .1814104
                        live_w_children |  -.0639217   .0191306    -3.34   0.003    -.1033218   -.0245215
                                 income |  -.0089259   .0069267    -1.29   0.209    -.0231917    .0053398
                                  _cons |   .5967404   .0957476     6.23   0.000     .3995445    .7939362
---------------------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        26          26           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. margins party_recode##Yc6_stayathom

Predictive margins                                       Number of obs = 4,002
Model VCE: Robust

Expression: Linear prediction, predict()

---------------------------------------------------------------------------------------------------------
                                        |            Delta-method
                                        |     Margin   std. err.      z    P>|z|     [95% conf. interval]
----------------------------------------+----------------------------------------------------------------
                           party_recode |
                                Repub.  |   .8890374   .0307062    28.95   0.000     .8288543    .9492205
                                Indep.  |   .7188182   .0317344    22.65   0.000     .6566199    .7810165
                                  Dem.  |    .608141   .0263311    23.10   0.000      .556533    .6597491
                                        |
             Yc6_stayathomerequirements |
                                     0  |   .7645114   .0319209    23.95   0.000     .7019476    .8270752
                                     1  |    .705485   .0323457    21.81   0.000     .6420886    .7688814
                                        |
party_recode#Yc6_stayathomerequirements |
                              Repub.#0  |   .8941387   .0436785    20.47   0.000     .8085304    .9797471
                              Repub.#1  |   .8837933   .0530806    16.65   0.000     .7797572    .9878294
                              Indep.#0  |   .7516092   .0453593    16.57   0.000     .6627066    .8405119
                              Indep.#1  |   .6851093   .0609301    11.24   0.000     .5656886      .80453
                                Dem.#0  |   .6562594   .0506828    12.95   0.000     .5569229     .755596
                                Dem.#1  |   .5586758   .0503828    11.09   0.000     .4599274    .6574242
---------------------------------------------------------------------------------------------------------

. marginsplot, saving(app2, replace) ///
> ci1opts(lc(green) lp(dash))  plot1opts(lc(green) connect(none) mc(green) mlcolor(green) msymbol(Dh)) ///
> ci2opts(lc(blue) lp(dash))  plot2opts(lc(blue) connect(none) mc(blue) mlcolor(blue) msymbol(Oh)) ///
> xtitle("") title("Predicted approval of Republican governor" "by whether stay-at-home order is in effect") plot3opts(lc(none)
>  mc(none)) ci3opts(col(none)) leg(pos(6) order(1 "Not in effect" 2 "In effect" 3 "") rows(1) rowgap(*1.5) colgap(*1.5))

Variables that uniquely identify margins: party_recode Yc6_stayathomerequirements
(file app2.gph not found)
file app2.gph saved

. 
.  
. *Columns 5 and 6
. reghdfe approvestate  party_recode##Yc4_restrictionsongatherings   ///
> LNpc_new_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live_
> w_children income ///
> if demgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  21,     23) =     617.52
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1382
                                                  Adj R-squared   =     0.1291
                                                  Within R-sq.    =     0.0959
Number of clusters (stateid) =         24         Root MSE        =     0.3858

                                                            (Std. err. adjusted for 24 clusters in stateid)
-----------------------------------------------------------------------------------------------------------
                                          |               Robust
                     approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
------------------------------------------+----------------------------------------------------------------
                             party_recode |
                                  Indep.  |   .0075118   .0720279     0.10   0.918    -.1414892    .1565128
                                    Dem.  |   .2554435    .012412    20.58   0.000     .2297673    .2811197
                                          |
           1.Yc4_restrictionsongatherings |   .1109684    .042472     2.61   0.016     .0231085    .1988284
                                          |
party_recode#Yc4_restrictionsongatherings |
                                Indep.#1  |   .0720368   .0896323     0.80   0.430    -.1133816    .2574553
                                  Dem.#1  |  -.0490044    .037431    -1.31   0.203    -.1264364    .0284275
                                          |
                      LNpc_new_cases_7day |   .0158655   .0086249     1.84   0.079    -.0019765    .0337074
                            out_workforce |    .037582   .0558542     0.67   0.508    -.0779611    .1531251
                                 employed |   .0000148   .0439631     0.00   1.000    -.0909298    .0909595
                                     male |  -.0653737   .0226384    -2.89   0.008    -.1122048   -.0185425
                                    age10 |   .0269777   .0129911     2.08   0.049     .0001036    .0538519
                               age_group4 |  -.0020309   .0551512    -0.04   0.971    -.1161197     .112058
                                  somecol |   .0416269   .0356492     1.17   0.255     -.032119    .1153729
                                       ba |   .0404042   .0280034     1.44   0.163    -.0175252    .0983336
                                     grad |   .1117035   .0338346     3.30   0.003     .0417113    .1816957
                                  AmerInd |   .1398154   .0790205     1.77   0.090    -.0236509    .3032817
                                    Asian |   .1457688   .0295907     4.93   0.000     .0845557    .2069819
                                    Black |  -.0131056   .0480634    -0.27   0.788    -.1125324    .0863212
                                     Hisp |   .0434185   .0352868     1.23   0.231    -.0295778    .1164147
                              Multiracial |  -.0473388   .0628558    -0.75   0.459     -.177366    .0826885
                          live_w_children |  -.0010133   .0189304    -0.05   0.958    -.0401737    .0381472
                                   income |   .0002196   .0060301     0.04   0.971    -.0122547    .0126938
                                    _cons |    .361322   .0811319     4.45   0.000     .1934878    .5291562
-----------------------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. margins party_recode##Yc4_restrictionsongatherings

Predictive margins                                       Number of obs = 5,234
Model VCE: Robust

Expression: Linear prediction, predict()

-----------------------------------------------------------------------------------------------------------
                                          |            Delta-method
                                          |     Margin   std. err.      z    P>|z|     [95% conf. interval]
------------------------------------------+----------------------------------------------------------------
                             party_recode |
                                  Repub.  |   .6640974   .0260868    25.46   0.000     .6129682    .7152267
                                  Indep.  |   .7386006   .0119062    62.04   0.000      .715265    .7619363
                                    Dem.  |   .8739688   .0136399    64.07   0.000      .847235    .9007025
                                          |
             Yc4_restrictionsongatherings |
                                       0  |   .6811269   .0296866    22.94   0.000     .6229422    .7393117
                                       1  |    .788448   .0020578   383.16   0.000     .7844149    .7924812
                                          |
party_recode#Yc4_restrictionsongatherings |
                                Repub.#0  |   .5609012   .0207642    27.01   0.000      .520204    .6015983
                                Repub.#1  |   .6718696    .028734    23.38   0.000     .6155519    .7281873
                                Indep.#0  |    .568413   .0797498     7.13   0.000     .4121063    .7247196
                                Indep.#1  |   .7514182   .0130699    57.49   0.000     .7258016    .7770348
                                  Dem.#0  |   .8163447   .0224997    36.28   0.000     .7722462    .8604432
                                  Dem.#1  |   .8783087   .0138753    63.30   0.000     .8511137    .9055037
-----------------------------------------------------------------------------------------------------------

. marginsplot, saving(app3, replace)  ///
> ci1opts(lc(green) lp(dash))  plot1opts(lc(green) connect(none) mc(green) mlcolor(green) msymbol(Dh)) ///
> ci2opts(lc(blue) lp(dash))  plot2opts(lc(blue) connect(none) mc(blue) mlcolor(blue) msymbol(Oh)) ///
> xtitle("") title("Predicted approval of Democratic governor" "by whether restrictions on gatherings are in place") plot3opts(
> lc(none) mc(none)) ci3opts(col(none)) leg(pos(6) order(1 "Not in effect" 2 "In effect" 3 "") rows(1) rowgap(*1.5) colgap(*1.5
> ))

Variables that uniquely identify margins: party_recode Yc4_restrictionsongatherings
(file app3.gph not found)
file app3.gph saved

. 
. reghdfe approvestate  party_recode##Yc6_stayathome ///
> LNpc_new_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live_
> w_children income ///
> if demgovernor==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  21,     23) =     151.46
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1399
                                                  Adj R-squared   =     0.1308
                                                  Within R-sq.    =     0.0977
Number of clusters (stateid) =         24         Root MSE        =     0.3855

                                                          (Std. err. adjusted for 24 clusters in stateid)
---------------------------------------------------------------------------------------------------------
                                        |               Robust
                   approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------------------+----------------------------------------------------------------
                           party_recode |
                                Indep.  |   .0304801   .0415721     0.73   0.471    -.0555183    .1164786
                                  Dem.  |   .1424321   .0488187     2.92   0.008     .0414429    .2434214
                                        |
           1.Yc6_stayathomerequirements |  -.1252241   .0753358    -1.66   0.110     -.281068    .0306199
                                        |
party_recode#Yc6_stayathomerequirements |
                              Indep.#1  |   .0851762    .062122     1.37   0.184    -.0433329    .2136854
                                Dem.#1  |   .1223371    .054411     2.25   0.034     .0097793    .2348949
                                        |
                    LNpc_new_cases_7day |   .0184215   .0091628     2.01   0.056    -.0005332    .0373762
                          out_workforce |   .0364078   .0558489     0.65   0.521    -.0791245    .1519401
                               employed |  -.0017278   .0443555    -0.04   0.969    -.0934841    .0900286
                                   male |  -.0674298   .0218397    -3.09   0.005    -.1126087   -.0222509
                                  age10 |   .0249985    .013188     1.90   0.071     -.002283    .0522799
                             age_group4 |  -.0006548   .0586533    -0.01   0.991    -.1219885    .1206789
                                somecol |   .0396302   .0359881     1.10   0.282    -.0348169    .1140773
                                     ba |    .033248   .0294184     1.13   0.270    -.0276086    .0941047
                                   grad |   .1055217   .0338225     3.12   0.005     .0355545    .1754889
                                AmerInd |   .1371867    .077333     1.77   0.089    -.0227888    .2971622
                                  Asian |   .1487309   .0297996     4.99   0.000     .0870858     .210376
                                  Black |  -.0141933   .0483396    -0.29   0.772    -.1141915    .0858049
                                   Hisp |   .0420193   .0357342     1.18   0.252    -.0319025    .1159412
                            Multiracial |  -.0361849    .061598    -0.59   0.563      -.16361    .0912403
                        live_w_children |  -.0035135   .0186721    -0.19   0.852    -.0421398    .0351127
                                 income |   .0011111   .0058102     0.19   0.850    -.0109081    .0131304
                                  _cons |   .5376811   .0960156     5.60   0.000     .3390577    .7363045
---------------------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. margins party_recode##Yc6_stayathom

Predictive margins                                       Number of obs = 5,234
Model VCE: Robust

Expression: Linear prediction, predict()

---------------------------------------------------------------------------------------------------------
                                        |            Delta-method
                                        |     Margin   std. err.      z    P>|z|     [95% conf. interval]
----------------------------------------+----------------------------------------------------------------
                           party_recode |
                                Repub.  |   .6612953   .0219936    30.07   0.000     .6181886     .704402
                                Indep.  |   .7403827   .0118992    62.22   0.000     .7170606    .7637047
                                  Dem.  |   .8735411   .0123058    70.99   0.000     .8494222    .8976601
                                        |
             Yc6_stayathomerequirements |
                                     0  |   .8067406   .0268732    30.02   0.000     .7540701     .859411
                                     1  |   .7606526   .0206214    36.89   0.000     .7202353    .8010699
                                        |
party_recode#Yc6_stayathomerequirements |
                              Repub.#0  |   .7327565   .0496939    14.75   0.000     .6353582    .8301548
                              Repub.#1  |   .6075324   .0377681    16.09   0.000     .5335083    .6815565
                              Indep.#0  |   .7632366   .0376312    20.28   0.000     .6894808    .8369924
                              Indep.#1  |   .7231888   .0303853    23.80   0.000     .6636347    .7827429
                                Dem.#0  |   .8751886   .0286961    30.50   0.000     .8189453    .9314319
                                Dem.#1  |   .8723017   .0193507    45.08   0.000      .834375    .9102283
---------------------------------------------------------------------------------------------------------

. marginsplot, saving(app4, replace) ///
> ci1opts(lc(green) lp(dash))  plot1opts(lc(green) connect(none) mc(green) mlcolor(green) msymbol(Dh)) ///
> ci2opts(lc(blue) lp(dash))  plot2opts(lc(blue) connect(none) mc(blue) mlcolor(blue) msymbol(Oh)) ///
> xtitle("") title("Predicted approval of Democratic governor" "by whether stay-at-home order is in place") plot3opts(lc(none) 
> mc(none)) ci3opts(col(none)) leg(pos(6) order(1 "Not in effect" 2 "In effect" 3 "") rows(1) rowgap(*1.5) colgap(*1.5))

Variables that uniquely identify margins: party_recode Yc6_stayathomerequirements
(file app4.gph not found)
file app4.gph saved

. 
. 
. grc1leg  app1.gph app2.gph app3.gph app4.gph     ///
> , imargin(2 2 2 2) row(2) col(2)  legendfrom(app1.gph) iscale(*.75) plotregion(color(white)) graphregion(color(white)) 

. graph export "figures\Figure S27.png", replace width(2200) height(1600)
file figures\Figure S27.png saved as PNG format

. 
. * Delete the intermediate files
. erase app1.gph

. erase app2.gph

. erase app3.gph

. erase app4.gph

. 
. 
. *****************
. *** Table S28 ***
. *****************
. 
. *Alternative Analyses for Table 2
. 
. clear

. use "data_gallup.dta"

. 
. 
. *Column 1 
. *result still holds for states for which gatherings is not the first policy (footnote/supp)
. gen gathfirst=1 if state=="Alabama" | state=="Alaska" | state=="California" | state=="Colorado" | state=="Delaware" | state==
> "Indiana" | state=="Iowa" | state=="Kansas" | state=="Maine" | state=="Maryland" | state=="Michigan" | state=="Minnesota" | s
> tate=="Missouri" | state=="New Jersey" | state=="New Mexico" | state=="North Carolina" | state=="Oregon" | state=="South Caro
> lina" | state=="Vermont" | state=="Wisconsin"
(95,632 missing values generated)

. replace gathfirst=0 if gathfirst==.
(95,632 real changes made)

. 
. reghdfe approvestate dem indep demrestrictionsongatherings indrestrictionsongatherings Yc4_restrictionsongatherings ///
> ZLNpc_new_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live
> _w_children income /// 
> if gopgovernor==1 & gathfirst==0 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 6 iterations)
warning: missing F statistic; dropped variables due to collinearity or too few clusters

HDFE Linear regression                            Number of obs   =      3,008
Absorbing 2 HDFE groups                           F(  21,     17) =          .
Statistics robust to heteroskedasticity           Prob > F        =          .
                                                  R-squared       =     0.1665
                                                  Adj R-squared   =     0.1524
                                                  Within R-sq.    =     0.1302
Number of clusters (stateid) =         18         Root MSE        =     0.4111

                                               (Std. err. adjusted for 18 clusters in stateid)
----------------------------------------------------------------------------------------------
                             |               Robust
        approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |  -.4164749   .0660986    -6.30   0.000    -.5559309    -.277019
                       indep |  -.1155677   .0499508    -2.31   0.033    -.2209546   -.0101808
 demrestrictionsongatherings |   .1775325   .0877245     2.02   0.059      -.00755    .3626151
 indrestrictionsongatherings |  -.0507315   .0869476    -0.58   0.567    -.2341748    .1327119
Yc4_restrictionsongatherings |  -.0236699   .0767911    -0.31   0.762    -.1856849    .1383451
        ZLNpc_new_cases_7day |  -.0585487   .0215819    -2.71   0.015    -.1040826   -.0130148
               out_workforce |   .1289154   .1146262     1.12   0.276    -.1129248    .3707556
                    employed |   .0966191   .1188359     0.81   0.427    -.1541027     .347341
                        male |   .0014044   .0194657     0.07   0.943    -.0396645    .0424734
                       age10 |   .0406185   .0066823     6.08   0.000       .02652    .0547169
                  age_group4 |  -.0887233   .0297626    -2.98   0.008    -.1515169   -.0259297
                     somecol |  -.0058439   .0361908    -0.16   0.874    -.0821999    .0705121
                          ba |   .0538529   .0482159     1.12   0.280    -.0478738    .1555795
                        grad |  -.0313927   .0452993    -0.69   0.498    -.1269659    .0641806
                     AmerInd |  -.0476044   .1096475    -0.43   0.670    -.2789404    .1837316
                       Asian |   .4062884    .114525     3.55   0.002     .1646618     .647915
                       Black |   .1300522   .0465878     2.79   0.013     .0317604    .2283439
                        Hisp |   .0543048   .0261341     2.08   0.053    -.0008334     .109443
                 Multiracial |  -.0634636   .1351164    -0.47   0.645    -.3485343    .2216071
             live_w_children |  -.0954236   .0226075    -4.22   0.001    -.1431213   -.0477259
                      income |  -.0112386   .0072264    -1.56   0.138     -.026485    .0040077
                       _cons |   .5814535   .1214188     4.79   0.000     .3252823    .8376247
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        18          18           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) replace keep(dem gop indep demrestrictionsongatherings goprestri
> ctionsongatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. *Columns 2 and 3, no state fixed effects
. reghdfe approvestate dem indep demrestrictionsongatherings indrestrictionsongatherings Yc4_restrictionsongatherings ZLNpc_new
> _cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live_w_childr
> en income ///
> if gopgovernor==1 [aw=WEIGHT], a(time) vce(cl stateid)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 1 HDFE group                            F(  21,     25) =     254.35
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1130
                                                  Adj R-squared   =     0.1056
                                                  Within R-sq.    =     0.1087
Number of clusters (stateid) =         26         Root MSE        =     0.4174

                                               (Std. err. adjusted for 26 clusters in stateid)
----------------------------------------------------------------------------------------------
                             |               Robust
        approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   -.416357   .0581275    -7.16   0.000    -.5360728   -.2966413
                       indep |  -.1259413   .0485974    -2.59   0.016    -.2260294   -.0258531
 demrestrictionsongatherings |   .1896378   .0814918     2.33   0.028     .0218023    .3574733
 indrestrictionsongatherings |   .0047606   .0811578     0.06   0.954     -.162387    .1719081
Yc4_restrictionsongatherings |  -.0587491   .0292397    -2.01   0.055    -.1189695    .0014713
        ZLNpc_new_cases_7day |  -.0315154   .0190743    -1.65   0.111    -.0707997    .0077688
               out_workforce |   .1351191   .1014778     1.33   0.195    -.0738783    .3441166
                    employed |    .118537   .1083834     1.09   0.285    -.1046827    .3417567
                        male |  -.0158546   .0201366    -0.79   0.438    -.0573266    .0256175
                       age10 |   .0320212   .0089831     3.56   0.002     .0135202    .0505223
                  age_group4 |  -.0500901   .0377272    -1.33   0.196    -.1277907    .0276104
                     somecol |  -.0015255   .0330641    -0.05   0.964    -.0696223    .0665713
                          ba |  -.0012768   .0503656    -0.03   0.980    -.1050067    .1024531
                        grad |  -.0180854   .0467264    -0.39   0.702    -.1143201    .0781494
                     AmerInd |  -.2585663   .1371124    -1.89   0.071    -.5409545     .023822
                       Asian |    .278803   .1166764     2.39   0.025     .0385036    .5191025
                       Black |   .1405546   .0442283     3.18   0.004     .0494648    .2316443
                        Hisp |   .0148017   .0235305     0.63   0.535    -.0336602    .0632637
                 Multiracial |  -.0435081   .1098201    -0.40   0.695    -.2696869    .1826707
             live_w_children |  -.0884156   .0200868    -4.40   0.000     -.129785   -.0470461
                      income |  -.0059715   .0063572    -0.94   0.357    -.0190643    .0071214
                       _cons |   .6499083   .0842146     7.72   0.000     .4764651    .8233516
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           0          13     |
-----------------------------------------------------+

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. reghdfe approvestate dem indep demstay indstay Yc6_stayathome ZLNpc_new_cases_7day out_workforce employed male age10 age_grou
> p4   somecol ba grad AmerInd Asian Black Hisp Multiracial live_w_children income ///
> if gopgovernor==1 [aw=WEIGHT], a(time) vce(cl stateid)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      4,002
Absorbing 1 HDFE group                            F(  21,     25) =     148.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1262
                                                  Adj R-squared   =     0.1189
                                                  Within R-sq.    =     0.1219
Number of clusters (stateid) =         26         Root MSE        =     0.4143

                                             (Std. err. adjusted for 26 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       dem |  -.1954733    .073882    -2.65   0.014     -.347636   -.0433105
                     indep |  -.0918987   .0522585    -1.76   0.091     -.199527    .0157296
 demstayathomerequirements |  -.1172779   .0810771    -1.45   0.160    -.2842593    .0497035
 indstayathomerequirements |   -.069224   .0920569    -0.75   0.459    -.2588189    .1203708
Yc6_stayathomerequirements |  -.0638712   .0253333    -2.52   0.018    -.1160462   -.0116963
      ZLNpc_new_cases_7day |  -.0243008    .014472    -1.68   0.106    -.0541065    .0055048
             out_workforce |   .1437771   .0928992     1.55   0.134    -.0475525    .3351067
                  employed |   .1202795   .0946373     1.27   0.215    -.0746296    .3151886
                      male |   -.015679   .0202681    -0.77   0.446     -.057422     .026064
                     age10 |   .0327188   .0078295     4.18   0.000     .0165935     .048844
                age_group4 |  -.0580727   .0347567    -1.67   0.107    -.1296554    .0135101
                   somecol |  -.0095519   .0325477    -0.29   0.772    -.0765852    .0574814
                        ba |  -.0032137   .0477219    -0.07   0.947    -.1014987    .0950713
                      grad |  -.0232577   .0435576    -0.53   0.598    -.1129662    .0664509
                   AmerInd |  -.2670987   .1541964    -1.73   0.096    -.5846722    .0504748
                     Asian |   .3149295   .1182221     2.66   0.013     .0714466    .5584124
                     Black |   .1370397   .0383847     3.57   0.001      .057985    .2160944
                      Hisp |   .0284518   .0291001     0.98   0.338     -.031481    .0883846
               Multiracial |  -.0505483   .1007593    -0.50   0.620     -.258066    .1569694
           live_w_children |  -.0844353   .0173424    -4.87   0.000    -.1201526   -.0487181
                    income |  -.0053473   .0066904    -0.80   0.432    -.0191264    .0084318
                     _cons |   .6364624   .0789352     8.06   0.000     .4738924    .7990324
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           0          13     |
-----------------------------------------------------+

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. *Column 4, Only SAHO states
. gen nostayathome=0

. replace nostayathome=1 if state=="Arizona" | state=="New Mexico" | state=="Utah" | state=="Nevada" | state=="Wyoming" | state
> =="North Dakota" | state=="South Daktoa" | state=="Nebraska" | state=="Kansas" | state=="Kowa" | state=="Arkansas" | state=="
> Mississippi" | state=="Maryland" | state=="Connecticut" | state=="Massachusetts" 
(25,147 real changes made)

. 
. reghdfe approvestate  dem indep demstay indstay Yc6_stayathome ZLNpc_new_cases_7day out_workforce employed male age10 age_gro
> up4   somecol ba grad AmerInd Asian Black Hisp Multiracial live_w_children income ///
> if gopgovernor==1 & nostay==0 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(MWFE estimator converged in 6 iterations)
warning: missing F statistic; dropped variables due to collinearity or too few clusters

HDFE Linear regression                            Number of obs   =      2,900
Absorbing 2 HDFE groups                           F(  21,     16) =          .
Statistics robust to heteroskedasticity           Prob > F        =          .
                                                  R-squared       =     0.1683
                                                  Adj R-squared   =     0.1540
                                                  Within R-sq.    =     0.1249
Number of clusters (stateid) =         17         Root MSE        =     0.4188

                                             (Std. err. adjusted for 17 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       dem |  -.2711786    .064423    -4.21   0.001    -.4077492   -.1346079
                     indep |  -.0875247   .0717884    -1.22   0.240    -.2397092    .0646598
 demstayathomerequirements |   -.023434     .05834    -0.40   0.693    -.1471093    .1002413
 indstayathomerequirements |  -.0773021   .0877639    -0.88   0.391    -.2633533    .1087491
Yc6_stayathomerequirements |   .0227379    .074298     0.31   0.764    -.1347667    .1802425
      ZLNpc_new_cases_7day |   -.053895   .0196584    -2.74   0.014    -.0955688   -.0122211
             out_workforce |   .0686312    .114438     0.60   0.557    -.1739664    .3112289
                  employed |    .038861   .1158967     0.34   0.742    -.2068291    .2845511
                      male |  -.0179057   .0273303    -0.66   0.522    -.0758433     .040032
                     age10 |   .0396093   .0091111     4.35   0.000     .0202946    .0589241
                age_group4 |   -.071894    .036077    -1.99   0.064    -.1483738    .0045859
                   somecol |  -.0033643   .0349251    -0.10   0.924    -.0774021    .0706736
                        ba |   .0037493    .053377     0.07   0.945    -.1094049    .1169034
                      grad |  -.0696908   .0541337    -1.29   0.216    -.1844491    .0450674
                   AmerInd |  -.3227074   .1601163    -2.02   0.061    -.6621388     .016724
                     Asian |   .4502144   .1404115     3.21   0.006     .1525553    .7478736
                     Black |   .1293461    .044392     2.91   0.010     .0352392     .223453
                      Hisp |   .0394667   .0283298     1.39   0.183    -.0205897    .0995232
               Multiracial |  -.1226215   .1292985    -0.95   0.357     -.396722     .151479
           live_w_children |  -.0418329   .0233931    -1.79   0.093    -.0914241    .0077582
                    income |  -.0060137   .0093498    -0.64   0.529    -.0258344     .013807
                     _cons |   .5739129   .1026133     5.59   0.000     .3563824    .7914435
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        17          17           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. *Column 5 and 6, gatherings according to whether considered avoiding gatherings
. gen avoidedgath=1 if C9B==1 | C9B==2
(139,386 missing values generated)

. replace avoidedgath=0 if C9B==3
(4,473 real changes made)

. 
. *If purely teamsmanship, then effect should extend to Dems who have not considered avoiding gatherings
. reghdfe approvestate  dem indep demrestrictionsongatherings indrestrictionsongatherings Yc4_restrictionsongatherings ZLNpc_ne
> w_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live_w_child
> ren income if gopgovernor==1 & avoidedgath==0 [aw=WEIGHT] , a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 9 iterations)

HDFE Linear regression                            Number of obs   =        476
Absorbing 2 HDFE groups                           F(  21,     24) =    6277.37
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3749
                                                  Adj R-squared   =     0.2947
                                                  Within R-sq.    =     0.1739
Number of clusters (stateid) =         25         Root MSE        =     0.3558

                                               (Std. err. adjusted for 25 clusters in stateid)
----------------------------------------------------------------------------------------------
                             |               Robust
        approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |   -.007988   .1288161    -0.06   0.951    -.2738514    .2578755
                       indep |  -.3889586   .2348689    -1.66   0.111    -.8737042     .095787
 demrestrictionsongatherings |  -.2517945   .1870245    -1.35   0.191    -.6377941    .1342052
 indrestrictionsongatherings |   .3496881   .2325988     1.50   0.146    -.1303722    .8297485
Yc4_restrictionsongatherings |  -.3525238   .2527675    -1.39   0.176    -.8742103    .1691626
        ZLNpc_new_cases_7day |  -.0211835    .060336    -0.35   0.729    -.1457109    .1033438
               out_workforce |   .3994786   .3260045     1.23   0.232    -.2733616    1.072319
                    employed |   .3236014   .3242349     1.00   0.328    -.3455866    .9927893
                        male |   -.100711   .1033142    -0.97   0.339    -.3139409     .112519
                       age10 |  -.0066517   .0243515    -0.27   0.787    -.0569107    .0436073
                  age_group4 |   .0682076   .1000549     0.68   0.502    -.1382957    .2747109
                     somecol |    .073625   .0805235     0.91   0.370    -.0925673    .2398172
                          ba |   .0723851   .0752523     0.96   0.346    -.0829281    .2276983
                        grad |   .0978274   .1037237     0.94   0.355    -.1162477    .3119025
                     AmerInd |  -.0646242   .3624921    -0.18   0.860    -.8127711    .6835228
                       Asian |  -.7327419   .2621369    -2.80   0.010    -1.273766    -.191718
                       Black |  -.0801664   .1030502    -0.78   0.444    -.2928516    .1325187
                        Hisp |     .07707   .0866596     0.89   0.383    -.1017866    .2559265
                 Multiracial |  -.5807297   .1768477    -3.28   0.003    -.9457254    -.215734
             live_w_children |    .047866   .0519144     0.92   0.366      -.05928     .155012
                      income |  -.0368458   .0147749    -2.49   0.020    -.0673397   -.0063519
                       _cons |   .9994176   .4802825     2.08   0.048     .0081632    1.990672
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        10           1           9     |
     stateid |        25          25           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. *but does hold for those who either have avoided or considered doing so
. reghdfe approvestate  dem indep demrestrictionsongatherings indrestrictionsongatherings Yc4_restrictionsongatherings ZLNpc_ne
> w_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live_w_child
> ren income if gopgovernor==1 & avoidedgath==1 [aw=WEIGHT] , a(time stateid) vce(cl stateid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      3,521
Absorbing 2 HDFE groups                           F(  21,     25) =      57.67
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2063
                                                  Adj R-squared   =     0.1930
                                                  Within R-sq.    =     0.1389
Number of clusters (stateid) =         26         Root MSE        =     0.3981

                                               (Std. err. adjusted for 26 clusters in stateid)
----------------------------------------------------------------------------------------------
                             |               Robust
        approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         dem |  -.4546334   .0643749    -7.06   0.000     -.587216   -.3220508
                       indep |  -.1044366   .0618238    -1.69   0.104    -.2317652     .022892
 demrestrictionsongatherings |   .2209073   .0781112     2.83   0.009     .0600342    .3817803
 indrestrictionsongatherings |  -.0690499   .0818613    -0.84   0.407    -.2376465    .0995467
Yc4_restrictionsongatherings |   -.017905   .1063208    -0.17   0.868    -.2368768    .2010668
        ZLNpc_new_cases_7day |  -.0561092   .0183175    -3.06   0.005    -.0938348   -.0183835
               out_workforce |   .1023035   .0980469     1.04   0.307    -.0996279    .3042348
                    employed |   .0947048   .1049259     0.90   0.375    -.1213941    .3108037
                        male |  -.0061451   .0202679    -0.30   0.764    -.0478876    .0355974
                       age10 |   .0444149   .0087376     5.08   0.000     .0264195    .0624103
                  age_group4 |  -.0632778   .0331481    -1.91   0.068    -.1315477     .004992
                     somecol |  -.0104486   .0377705    -0.28   0.784    -.0882385    .0673413
                          ba |  -.0045582   .0481014    -0.09   0.925    -.1036249    .0945086
                        grad |  -.0454065   .0474795    -0.96   0.348    -.1431924    .0523795
                     AmerInd |  -.3325179   .1793634    -1.85   0.076    -.7019237    .0368879
                       Asian |   .4149075   .1279658     3.24   0.003      .151357     .678458
                       Black |   .1410459   .0422299     3.34   0.003     .0540718    .2280201
                        Hisp |    .046234   .0335427     1.38   0.180    -.0228485    .1153165
                 Multiracial |   .0458933   .0615951     0.75   0.463    -.0809642    .1727509
             live_w_children |  -.0749813   .0228129    -3.29   0.003    -.1219653   -.0279974
                      income |  -.0034668   .0077194    -0.45   0.657    -.0193652    .0124317
                       _cons |   .5486792   .1379131     3.98   0.001     .2646418    .8327165
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        13           1          12     |
     stateid |        26          26           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. *Column 7, result on SAHOs holds for states that did not include it as a first policy
. *Hawaii is the only state to enact a SAHO as a first policy
. reghdfe approvestate  gop indep  gopstay indstay Yc6_stayathome ///
> ZLNpc_new_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live
> _w_children income ///
> if demgovernor==1 & state!="Hawaii" [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 5 iterations)

HDFE Linear regression                            Number of obs   =      5,210
Absorbing 2 HDFE groups                           F(  21,     22) =      59.65
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1316
                                                  Adj R-squared   =     0.1225
                                                  Within R-sq.    =     0.0930
Number of clusters (stateid) =         23         Root MSE        =     0.3865

                                             (Std. err. adjusted for 23 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       gop |  -.1398059   .0477337    -2.93   0.008    -.2387996   -.0408122
                     indep |  -.1186768   .0471882    -2.51   0.020     -.216539   -.0208145
 gopstayathomerequirements |  -.1060929   .0540898    -1.96   0.063    -.2182683    .0060825
 indstayathomerequirements |   .0023586   .0654738     0.04   0.972    -.1334258     .138143
Yc6_stayathomerequirements |  -.0188795   .0398503    -0.47   0.640    -.1015241     .063765
      ZLNpc_new_cases_7day |   .0288687   .0146904     1.97   0.062    -.0015973    .0593348
             out_workforce |    .033513   .0557552     0.60   0.554    -.0821162    .1491421
                  employed |  -.0061944   .0444947    -0.14   0.891    -.0984707     .086082
                      male |    -.06934   .0219155    -3.16   0.004    -.1147899   -.0238901
                     age10 |   .0243101   .0130814     1.86   0.077    -.0028191    .0514392
                age_group4 |   .0022684   .0584076     0.04   0.969    -.1188614    .1233983
                   somecol |   .0390067   .0360871     1.08   0.291    -.0358333    .1138468
                        ba |   .0372483   .0288897     1.29   0.211    -.0226653    .0971619
                      grad |   .1102447   .0329352     3.35   0.003     .0419414     .178548
                   AmerInd |   .1115466   .0666514     1.67   0.108    -.0266799    .2497732
                     Asian |   .1564636   .0301552     5.19   0.000     .0939256    .2190017
                     Black |  -.0096661   .0487752    -0.20   0.845    -.1108196    .0914875
                      Hisp |   .0424242   .0352919     1.20   0.242    -.0307668    .1156152
               Multiracial |  -.0387492   .0626534    -0.62   0.543    -.1686844    .0911859
           live_w_children |  -.0074476   .0190031    -0.39   0.699    -.0468577    .0319625
                    income |    .002103   .0057982     0.36   0.720    -.0099219    .0141278
                     _cons |   .7510982   .0927914     8.09   0.000     .5586606    .9435359
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        23          23           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. *Columns 8 and 9, what if no state fixed effects
. reghdfe approvestate  gop indep goprestrictionsongatherings indrestrictionsongatherings Yc4_restrictionsongatherings  ///
> ZLNpc_new_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live
> _w_children income ///
> if demgovernor==1 [aw=WEIGHT], a(time) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 1 HDFE group                            F(  21,     23) =   20220.07
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.0999
                                                  Adj R-squared   =     0.0944
                                                  Within R-sq.    =     0.0900
Number of clusters (stateid) =         24         Root MSE        =     0.3935

                                               (Std. err. adjusted for 24 clusters in stateid)
----------------------------------------------------------------------------------------------
                             |               Robust
        approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------------+----------------------------------------------------------------
                         gop |  -.2370474    .016947   -13.99   0.000    -.2721049   -.2019899
                       indep |  -.2918776   .0791838    -3.69   0.001    -.4556818   -.1280735
 goprestrictionsongatherings |    .045367   .0369211     1.23   0.232    -.0310101     .121744
 indrestrictionsongatherings |   .1734721   .0842751     2.06   0.051    -.0008642    .3478083
Yc4_restrictionsongatherings |   .0229973   .0313861     0.73   0.471    -.0419298    .0879244
        ZLNpc_new_cases_7day |   .0091854   .0111025     0.83   0.417    -.0137819    .0321528
               out_workforce |   .0264456   .0560103     0.47   0.641    -.0894206    .1423118
                    employed |   -.015549   .0469269    -0.33   0.743    -.1126247    .0815267
                        male |  -.0613192   .0229145    -2.68   0.013    -.1087214   -.0139171
                       age10 |   .0275903   .0133517     2.07   0.050    -.0000298    .0552103
                  age_group4 |   .0018463    .056672     0.03   0.974    -.1153886    .1190812
                     somecol |   .0419832   .0367061     1.14   0.264    -.0339493    .1179156
                          ba |   .0524919    .028014     1.87   0.074    -.0054595    .1104432
                        grad |   .1206983   .0349657     3.45   0.002     .0483663    .1930303
                     AmerInd |    .055665   .0524373     1.06   0.299    -.0528098    .1641397
                       Asian |   .1405557    .020212     6.95   0.000      .098744    .1823675
                       Black |   .0054474   .0463487     0.12   0.907    -.0904322     .101327
                        Hisp |   .0417083   .0315432     1.32   0.199    -.0235437    .1069603
                 Multiracial |  -.0559296   .0621027    -0.90   0.377    -.1843988    .0725396
             live_w_children |  -.0009434   .0212741    -0.04   0.965    -.0449522    .0430655
                      income |   .0011998   .0057807     0.21   0.837    -.0107585    .0131582
                       _cons |   .6861706   .0980795     7.00   0.000     .4832776    .8890635
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           0          12     |
-----------------------------------------------------+

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. reghdfe approvestate  gop indep  gopstay indstay Yc6_stayathome ///
> ZLNpc_new_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live
> _w_children income ///
> if demgovernor==1 [aw=WEIGHT], a(time) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 1 HDFE group                            F(  21,     23) =     293.55
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1015
                                                  Adj R-squared   =     0.0960
                                                  Within R-sq.    =     0.0917
Number of clusters (stateid) =         24         Root MSE        =     0.3931

                                             (Std. err. adjusted for 24 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       gop |  -.1293431   .0467387    -2.77   0.011    -.2260295   -.0326566
                     indep |  -.1397558   .0488665    -2.86   0.009    -.2408439   -.0386677
 gopstayathomerequirements |  -.1197347   .0521589    -2.30   0.031    -.2276336   -.0118358
 indstayathomerequirements |   .0227577   .0687767     0.33   0.744    -.1195178    .1650332
Yc6_stayathomerequirements |   .0358489   .0340325     1.05   0.303    -.0345527    .1062505
      ZLNpc_new_cases_7day |   .0111746   .0126493     0.88   0.386    -.0149926    .0373417
             out_workforce |   .0242053   .0564452     0.43   0.672    -.0925605     .140971
                  employed |  -.0164619   .0464847    -0.35   0.726    -.1126228    .0796989
                      male |  -.0632434    .022212    -2.85   0.009    -.1091923   -.0172944
                     age10 |   .0262788   .0130843     2.01   0.056    -.0007881    .0533456
                age_group4 |   .0024222   .0582003     0.04   0.967    -.1179744    .1228188
                   somecol |   .0406544   .0364396     1.12   0.276    -.0347267    .1160355
                        ba |   .0481765   .0286983     1.68   0.107    -.0111904    .1075435
                      grad |   .1173417   .0335896     3.49   0.002     .0478563    .1868271
                   AmerInd |   .0581092   .0541858     1.07   0.295    -.0539828    .1702011
                     Asian |   .1426351    .024267     5.88   0.000      .092435    .1928351
                     Black |   .0041116   .0468819     0.09   0.931    -.0928711    .1010942
                      Hisp |   .0401313   .0330348     1.21   0.237    -.0282065    .1084691
               Multiracial |  -.0473884   .0623875    -0.76   0.455    -.1764468    .0816701
           live_w_children |  -.0054727   .0210658    -0.26   0.797    -.0490506    .0381051
                    income |   .0017757   .0056483     0.31   0.756    -.0099087      .01346
                     _cons |   .6970924   .0962564     7.24   0.000     .4979709    .8962138
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           0          12     |
-----------------------------------------------------+

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. *Column 10, only SAHO states
. reghdfe approvestate  gop indep  gopstay indstay Yc6_stayathome ///
> ZLNpc_new_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live
> _w_children income ///
> if demgovernor==1 & nostay==0 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 6 iterations)
warning: missing F statistic; dropped variables due to collinearity or too few clusters

HDFE Linear regression                            Number of obs   =      4,870
Absorbing 2 HDFE groups                           F(  21,     19) =          .
Statistics robust to heteroskedasticity           Prob > F        =          .
                                                  R-squared       =     0.1261
                                                  Adj R-squared   =     0.1168
                                                  Within R-sq.    =     0.0879
Number of clusters (stateid) =         20         Root MSE        =     0.3844

                                             (Std. err. adjusted for 20 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       gop |  -.1197687   .0493171    -2.43   0.025    -.2229907   -.0165468
                     indep |  -.0720078   .0436669    -1.65   0.116    -.1634037    .0193881
 gopstayathomerequirements |  -.1294946   .0547974    -2.36   0.029    -.2441868   -.0148024
 indstayathomerequirements |  -.0444418   .0624385    -0.71   0.485     -.175127    .0862434
Yc6_stayathomerequirements |   .0037547   .0394058     0.10   0.925    -.0787227     .086232
      ZLNpc_new_cases_7day |   .0305727   .0156148     1.96   0.065    -.0021094    .0632548
             out_workforce |   .0472393   .0635304     0.74   0.466    -.0857314    .1802099
                  employed |   .0101069    .049294     0.21   0.840    -.0930666    .1132804
                      male |  -.0656269   .0223589    -2.94   0.008    -.1124246   -.0188292
                     age10 |   .0209685   .0123924     1.69   0.107    -.0049692    .0469061
                age_group4 |   .0120154   .0582844     0.21   0.839    -.1099753    .1340061
                   somecol |   .0308665   .0391961     0.79   0.441    -.0511719    .1129048
                        ba |   .0285051   .0299811     0.95   0.354    -.0342462    .0912563
                      grad |   .0983796   .0352475     2.79   0.012     .0246058    .1721533
                   AmerInd |   .0647903   .0766987     0.84   0.409    -.0957419    .2253226
                     Asian |   .1513613   .0318936     4.75   0.000     .0846073    .2181153
                     Black |  -.0132927   .0526628    -0.25   0.803    -.1235173    .0969318
                      Hisp |    .027507   .0358012     0.77   0.452    -.0474259    .1024398
               Multiracial |  -.0312177   .0633016    -0.49   0.628    -.1637095    .1012741
           live_w_children |  -.0169735   .0195817    -0.87   0.397    -.0579584    .0240115
                    income |   .0031505   .0058752     0.54   0.598    -.0091465    .0154474
                     _cons |   .7418721   .0973889     7.62   0.000     .5380348    .9457093
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        20          20           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. *Columns 11 and 12, party teamsmanship
. 
. *versus not very likely to do so (somewhat likely, somehwat unlikely, or very unlikely)
. reghdfe approvestate  gop indep  gopstay indstay Yc6_stayathome ///
> ZLNpc_new_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live
> _w_children income ///
> if demgovernor==1 & C4_1>1 & C4_1<5 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 2 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      1,698
Absorbing 2 HDFE groups                           F(  21,     23) =     340.94
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1892
                                                  Adj R-squared   =     0.1626
                                                  Within R-sq.    =     0.0957
Number of clusters (stateid) =         24         Root MSE        =     0.4392

                                             (Std. err. adjusted for 24 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       gop |  -.1281344    .098786    -1.30   0.207    -.3324888    .0762201
                     indep |  -.1426387   .0668302    -2.13   0.044    -.2808875   -.0043899
 gopstayathomerequirements |  -.1865524   .0885826    -2.11   0.046    -.3697995   -.0033054
 indstayathomerequirements |  -.0598863   .1179277    -0.51   0.616    -.3038384    .1840658
Yc6_stayathomerequirements |   .0122389   .0631543     0.19   0.848    -.1184057    .1428835
      ZLNpc_new_cases_7day |   .0523723   .0157022     3.34   0.003     .0198899    .0848548
             out_workforce |   .1525794   .1394329     1.09   0.285    -.1358595    .4410183
                  employed |    .059368   .1284689     0.46   0.648    -.2063901    .3251262
                      male |   .0120749   .0302569     0.40   0.694    -.0505163    .0746661
                     age10 |   .0203184    .020629     0.98   0.335    -.0223559    .0629928
                age_group4 |  -.0116165   .1090245    -0.11   0.916     -.237151    .2139179
                   somecol |   .0982405   .0555394     1.77   0.090    -.0166515    .2131325
                        ba |   .0379999   .0658509     0.58   0.570    -.0982232    .1742229
                      grad |   .0965414   .0647134     1.49   0.149    -.0373285    .2304112
                   AmerInd |   .2473654   .1189028     2.08   0.049     .0013961    .4933346
                     Asian |   .2305825   .0600674     3.84   0.001     .1063236    .3548415
                     Black |   .0639582    .105764     0.60   0.551    -.1548312    .2827476
                      Hisp |   .0250027   .0641211     0.39   0.700     -.107642    .1576473
               Multiracial |   .0968188   .0883934     1.10   0.285    -.0860369    .2796745
           live_w_children |  -.0134891   .0417064    -0.32   0.749    -.0997655    .0727872
                    income |   .0101774   .0106703     0.95   0.350    -.0118958    .0322505
                     _cons |   .5156606   .1936258     2.66   0.014     .1151152     .916206
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        11           1          10     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. *respondents who are very likely to isolate if public health officials recommend doing so
. reghdfe approvestate  gop indep  gopstay indstay Yc6_stayathome ///
> ZLNpc_new_cases_7day out_workforce employed male age10 age_group4   somecol ba grad AmerInd Asian Black Hisp Multiracial live
> _w_children income ///
> if demgovernor==1 & C4_1==1 [aw=WEIGHT], a(time stateid) vce(cl stateid)
(dropped 1 singleton observations)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      3,531
Absorbing 2 HDFE groups                           F(  21,     23) =     138.08
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1139
                                                  Adj R-squared   =     0.0998
                                                  Within R-sq.    =     0.0612
Number of clusters (stateid) =         24         Root MSE        =     0.3228

                                             (Std. err. adjusted for 24 clusters in stateid)
--------------------------------------------------------------------------------------------
                           |               Robust
      approvestateresponse | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                       gop |  -.0783076   .0399324    -1.96   0.062    -.1609142    .0042989
                     indep |  -.0496112   .0489338    -1.01   0.321    -.1508385    .0516161
 gopstayathomerequirements |  -.0482727   .0630937    -0.77   0.452     -.178792    .0822466
 indstayathomerequirements |  -.0134912   .0654182    -0.21   0.838    -.1488191    .1218367
Yc6_stayathomerequirements |  -.0138232   .0475295    -0.29   0.774    -.1121454    .0844989
      ZLNpc_new_cases_7day |   .0148583   .0189994     0.78   0.442    -.0244449    .0541615
             out_workforce |  -.0405682   .0458167    -0.89   0.385    -.1353472    .0542108
                  employed |  -.0075946   .0394173    -0.19   0.849    -.0891354    .0739463
                      male |  -.0965753   .0292954    -3.30   0.003    -.1571775   -.0359731
                     age10 |   .0193893   .0135038     1.44   0.165    -.0085454    .0473241
                age_group4 |   .0062485     .03994     0.16   0.877    -.0763736    .0888707
                   somecol |   .0111241   .0381653     0.29   0.773    -.0678269    .0900751
                        ba |   -.002949   .0365769    -0.08   0.936     -.078614     .072716
                      grad |   .0611274   .0433499     1.41   0.172    -.0285486    .1508034
                   AmerInd |   .0271956   .0703624     0.39   0.703    -.1183602    .1727514
                     Asian |    .093212   .0402583     2.32   0.030     .0099313    .1764927
                     Black |  -.0146598   .0295287    -0.50   0.624    -.0757446     .046425
                      Hisp |   .0550572   .0307396     1.79   0.086    -.0085325     .118647
               Multiracial |  -.0838921   .0648197    -1.29   0.208    -.2179818    .0501976
           live_w_children |  -.0042664   .0228996    -0.19   0.854    -.0516377     .043105
                    income |  -.0028849   .0078354    -0.37   0.716    -.0190938    .0133239
                     _cons |   .8785578    .089747     9.79   0.000     .6929019    1.064214
--------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
        time |        12           1          11     |
     stateid |        24          24           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 using "tables\Table S28.xls", excel adjr2 lab dec(3) keep(dem gop indep demrestrictionsongatherings goprestrictionson
> gatherings indrestrictionsongatherings Yc4_restrictionsongatherings demstay gopstay indstay Yc6_stayathome)
tables\Table S28.xls
dir : seeout

. 
. 
. 
end of do-file

. log close
      name:  <unnamed>
       log:  C:\Users\brandice\Dropbox\Brandice_Luca\Covid partisanship paper\Replication files\Luca replicate\cwrm_replication
> .log
  log type:  text
 closed on:  26 May 2025, 13:37:52
-------------------------------------------------------------------------------------------------------------------------------
